Miracle-dz/UniFAR-FTUs huggingface dataset:
Coalition Formation Games for Coordinated Service in Realistic Small Cell Propagation Topologies

The densification of modern wireless networks into a dense ecosystem of small cells imposes challenges for the reliable service and high quality of experience of its users as it can result into severe intercell interference, especially for users scattered on the cell edges. Joint Transmission Coordinated Multipoint (JT-CoMP) is a technique that can be deployed to form cooperating clusters of transmission points, enabling them to jointly transmit data to significantly mitigate this type of interference for these users. However, JT-CoMP stresses the backhaul links and radio resources are limited, meaning that, with incautious clustering, the data rates for cell edge users may not improve, while the data rates for the non-cell edge users may severely decrease. To tackle these drawbacks, a dynamic coalition formation algorithm is proposed to form the appropriate transmission point clusters to implement JT-CoMP. Furthermore, to ensure reliable service for all the network’s users, the case where JT-CoMP is enhanced with the capability to serve users based on their selected application is examined. The proposed scheme’s adaptability and capability to increase cell edge user throughput is then tested and compared to the non JT-CoMP case, a JT-CoMP scheme with static clustering and a JT-CoMP scheme with greedy clustering for a user mobility scenario. To obtain more reliable and accurate results of the JT-CoMP deployment, physical layer parameters retrieved from a fully deterministic physical layer radio planning tool (TruNET wireless) are imported for our simulations.
Differential effects of mindfulness meditation conditions on repetitive negative thinking and subjective time perspective: a randomized active-controlled study

Abstract Objective Preliminary findings suggest that different kinds of meditation could work on diverse cognitive and psychological processes. The present study aimed at disentangling the effects of three mindfulness techniques on mental rumination and subjective time perspective. Design: 75 young healthy participants were randomly assigned to one of four conditions: mindful breathing, body scan, observing-thoughts meditation and an active control condition. The meditation groups practiced mindfulness daily and attended weekly group meetings for 8 weeks, while the control group was involved in reading and discussing a book about mindfulness. Main outcome measures: Self-report measures of mindfulness skills, ruminative thinking, attitude towards time, anxiety, depression and personality traits. Results: In all meditation conditions, analysis of covariance showed a significant improvement in mindfulness skills compared to the control group. We found a specific effect of mindful breathing in reducing participants’ tendency to brooding and in increasing their positive vision of the future, compared to all other conditions. Conclusions: As expected, we found some differential effects: breathing meditation helped practitioners to train more effectively their ability to disengage from maladaptive ruminative thoughts, which could be reflected in a more optimistic attitude toward the future. These results provide useful information to structure better mindfulness-based interventions.
ACOA-AFSA Fusion Dynamic Coded Cooperation Routing for Different Scale Multi-Hop Underwater Acoustic Sensor Networks

The limited energy supply of underwater nodes is one of the key issues for the multi-hop underwater acoustic sensor networks (UWA-SN). In this paper, the fusion scheme based on ant colony optimization algorithm (ACOA), artificial fish swarm algorithm (AFSA) and dynamic coded cooperation (DCC) strategy, named as ACOA-AFSA fusion DCC routing algorithm, has been proposed for routing in the multi-hop UWA-SN, aiming at simultaneously reducing the energy consumption and enhancing the robustness. In the proposed ACOA-AFSA fusion DCC routing algorithm, the randomness of the AFSA and the positive feedback mechanism of the ACOA enable the algorithm to find the global optimal routing more efficient and accurate. In addition, most existing routing protocols consider the large-scale networks (more than 100 nodes), while the medium- and small- scale networks (less than 100 nodes) are more practical in nowadays’ multi-hop UWA-SN. The network scale affects the optimal design of routing protocols in terms of energy saving. Considering the practical situation, we compare the proposed scheme with other four existing artificial intelligence (AI) routing algorithms in the medium- and small- scale multi-hop UWA-SN, which is instructive for application of AI in practical multi-hop UWA-SN. The simulation results show that the proposed ACOA-AFSA fusion DCC routing algorithm can reduce the energy consumption by 40.1% compared to that with non-cooperative strategy in the multi-hop UWA-SN with 20 nodes. The proposed routing algorithm also consumes less energy than other four existing AI routing algorithms in the medium-scale multi-hop UWA-SN with 50 nodes or 100 nodes. However, for the small-scale case with 10 nodes, the advantage is not very obvious. In the meantime, the proposed ACOA-AFSA fusion DCC algorithm is compatible with the ACOA-AFSA fusion non-cooperative algorithm, and the complexity is acceptable, which is very appealing to the time-varying marine environments.
An Efficient and Parallel Electromagnetic Solver for Complex Interconnects in Layered Media

A novel parallel solver based on the adaptive integral method (AIM) is proposed for the electromagnetic analysis of electrical interconnects in layered media. We show that graph partitioning techniques can be used to optimally distribute, across thousands of processes, the computations related to both matrix filling and system solution. The proposed workload distribution strategy is compared to existing techniques through a scalability study on a large realistic interposer model in layered media.
Conventional Machine Learning Techniques with Features Engineering for Preventive Larynx Cancer Detection

Larynx cancer is developed from precancerous state. Some precancerous lesions such as Keratosis, Leukoplakia, Ery-throlplakia, Papiloma virus, etc., can be transformed into a cancer if they are note treated in time. In this paper, we propose a non-intrusive technique to detect precancerous lesions at an earlier stage. Hence, these lesions can be treated as soon as possible. The idea is based on the analysis of the human voice in order to detect pertinent acoustic features able to discriminate pathological voices with precancerous lesions from normal ones. We have tested a large number of speech acoustic features. A feature engineering methodology leads us to choose the most pertinent features. To detect mentioned lesions, several classification techniques are tested. Experimental results show the validity of the idea.
An Experimental Study for Algorithm of Finding for Resident-Tracking Robot System

Among the advanced countries, especially in Japan, we are facing on the decreasing birthrate and aging population ahead of the world. In recent, population of single-living elder, and elderly people have been taking care by same-aged person, have been actualized. Unfortunately, the population of caregivers is decreasing according to year. In this situation, the Elderly Person Watching System has been focused on. Especially, Robotics, Internet of Things, and Artificial Intelligence technology have been having high affinity with this system. In this study, firstly, the person watching robot system will be developed. In detail, in this paper, the flexible-analyze system will be focused on. In the algorithm, a resident-tracking task and an energy-saving task are holding. The whole tasks are working based on Reinforcement Learning. Thus, the behavior algorithm of the person watching robot system will be developed. In detail, in this paper, the flexible-analyze system will be focused on. In the algorithm, a resident-tracking task and an energy-saving task are holding. From the verification experiment, the simulation results showed the proposed method has been acquired actions to switch the desired task.
Targeting Proteases for Treating COVID-19

The unprecedented pandemic of coronavirus disease 2019 (COVID-19) demands effective treatment for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The infection of SARS-CoV-2 critically depends on diverse viral or host proteases, which mediate viral entry, viral protein maturation, as well as the pathogenesis of the viral infection. Endogenous and exogenous agents targeting for proteases have been proved to be effective toward a variety of viral infections ranging from HIV to influenza virus, suggesting protease inhibitors as a promising antiviral treatment for COVID-19. In this Review, we discuss how host and viral proteases participated in the pathogenesis of COVID-19 as well as the prospects and ongoing clinical trials of protease inhibitors as treatments.
Panda: Reinforcement Learning-Based Priority Assignment for Multi-Processor Real-Time Scheduling

Recently, deep reinforcement learning (RL) technologies have been considered as a feasible solution for tackling combinatorial problems in various research and engineering areas. Motivated by this recent success of RL-based approaches, in this paper, we focus on how to utilize RL technologies in the context of real-time system research. Specifically, we first formulate the problem of fixed-priority assignments for multi-processor real-time scheduling, which has long been considered challenging in the real-time system community, as a combinatorial problem. We then propose the RL-based priority assignment model Panda that employs (i) a taskset embedding mechanism driven by attention-based encoder-decoder deep neural networks, hence enabling to efficiently extract useful features from the dynamic relation of periodic tasks. We also present two optimization schemes tailored to adopt RL for real-time task scheduling problems: (ii) the response time analysis (RTA)-based policy gradient RL and guided learning schemes, which facilitate the training processes of the Panda model. To the best of our knowledge, our approach is the first to employ RL for real-time task scheduling. Through various experiments, we show that Panda is competitive with well-known heuristic algorithms for real-time task scheduling upon a multi-processor platform, and it often outperforms them in large-scale non-trivial settings, e.g., achieving an average 7.7% enhancement in schedulability ratio for a testing system configuration of 64-sized tasksets and an 8-processor platform.
Correlates of expressed emotions as perceived by patients with bipolar disorder

Aim: To evaluate expressed emotions (EEs) as perceived by the patients and its correlates among patients with bipolar disorder (BD). Methodology: One hundred patients diagnosed with BD were assessed on the Perceived Criticism Measure (PCM), Family emotional involvement and criticism scale (FEICS), Brief dyadic scale for expressed emotions (BDSEE) and Vulnerability for abuse screening scale (VASS) to assess EE and possible abuse by the caregivers. Caregivers were evaluated on family burden interview schedule and family coping questionnaire. Results: Longer duration of illness (Pearson’s correlation coefficient: −0.335; p = .001***) and longer duration of treatment (Pearson’s correlation coefficient: −0.317; p = .001***) were associated with significantly lower perceived criticism as assessed by FEICS. Higher use of coping mechanisms such as coercion, avoidance and resignation by caregivers were associated with the higher perception of EE, whereas the use of coping mechanisms such as information seeking, communication, and social involvement by the caregivers was associated with the perception of lower EE among the patients. Higher caregiver burden was associated with a higher perception of the EE by the patients. Higher perception of abuse by the patients was associated with higher EE. Conclusions: Present study suggests that higher use of maladaptive coping, caregiver burden, and abuse has a significant impact on the EE. Accordingly, psychosocial interventions need to focus on caregivers to reduce EE.
Deletion of NKX3.1 via CRISPR/Cas9 Induces Prostatic Intraepithelial Neoplasia in C57BL/6 Mice

Several techniques have been employed for deletion of the NKX3.1 gene, resulting in developmental defects of the prostate, including alterations in ductal branching morphogenesis and prostatic secretions as well as epithelial hyperplasia and dysplasia. To investigate whether the CRISPR/Cas9-mediated technique can be applied to study prostate carcinogenesis through exon I deletion of NKX3.1 gene, alterations in the prostatic intraepithelial neoplasia (PIN) and their regulatory mechanism were observed in the prostate of NKX3.1 knockout (KO) mice produced by the CRISPR/Cas9-mediated NKX3.1 mutant gene, at the ages of 16 and 24 weeks. The weight of dorsal-lateral prostate (DLP) and anterior prostate (AP) were observed to be increased in only the 24 weeks KO mice, although morphogenesis was constant in all groups. Obvious PIN 1 and 2 lesions were frequently detected in prostate of the 24 weeks KO mice, as compared with the same age wild type (WT) mice. Ki67, a key indicator for PIN, was densely stained in the epithelium of prostate in the 24 weeks KO mice, while the expression of p53 protein was suppressed in the same group. Also, both the 16 and 24 weeks KO mice reveal inhibition of the PI3K/AKT/mTOR pathway in the prostate. However, prostate specific antigen (PSA) levels and Bax/Bcl-2 expressions were decreased in the prostate of 16 weeks KO mice, and were increased in only the 24 weeks KO mice. Taken together, the results of the present study provide additional evidence that CRISPR/Cas9-mediated exon 1 deletion of the NKX3.1 gene successfully induces PIN lesions, along with significant alterations of Ki67 expression, EGFR signaling pathway, and cancer-regulated proteins.
Influence of Maternal Exposure to Malaria Social and Behavioral Change Messages and Effectiveness of Communication Media on Bed Net Use and Malaria Infection in Malawi

Background Malawi is a malaria-endemic country. A national malaria communication strategy was adopted to disseminate malaria messages with the aim of improving knowledge and adoption of malaria interventions. Objective To examine the effect of maternal exposure to malaria messages and the medium through which such messages are delivered on insecticide-treated net (ITN) use and malaria infection among children under 5 years of age in Malawi. Methodology Utilizing the data from the 2017 Malawi Malaria Indicator Survey, 2,055 children (aged under 5 years) and 1,886 children (aged 6–59 months) were analyzed for ITN use and malaria infection outcomes, respectively. Components of exposure to malaria messages were tested for association with ITN use and malaria infection outcomes using multiple logistic regression models. Results Children whose mothers had reported hearing any malaria-related message in the past 6 months were more likely to sleep under an ITN and less likely to have malaria infection compared with those whose mothers had not heard any malaria-related message. Region and sex of the child were effect modifiers on the relationship between exposure to any malaria-related message and malaria infection. Knowledge regarding cause or protection methods partially mediated the relationship between exposure to any malaria message and malaria infection. Discussion and Conclusion Health workers were an effective communication channel. Strengthening topic-specific malaria messages and building the capacity of health workers while alternately strengthening other message outlets may prove vital for effective malaria communication.
An apparent-time study of an ongoing sound change in Seoul Korean: A prosodic account

In present-day Seoul Korean, the primary phonetic feature for the lenis–aspirated stop distinction is shifting from VOT to F0. Some previous studies have considered this sound change to be a tonogenesis, whereby the low-level F0 perturbation has developed into tonal features (L for the lenis and H for the aspirated) in the segmental phonology. They, however, have examined the stop distinction only at a phrase- or utterance-initial position. We newly explore the sound change in relation to various prosodic structural factors (position and prominence). Apparent-time production data were recorded from four speaker groups: young female, young male, old female, old male. The way the speakers use VOT versus F0 indeed varies as a function of position and prominence. Crucially, in all groups, VOT is still used for the lenis–aspirated distinction phrase-medially due to the lenis stop voicing. This role of VOT, however, is found only in the non-prominent (unfocused) condition, in which the F0 difference is reduced to a low-level perturbation effect. In the prominent (focused) context in which tones come into play, the role of VOT diminishes, led by young female speakers. These can be interpreted as a prosodically-conditioned, complementary use of the features to maintain sufficient contrast. Importantly, however, the tonal difference under focus is not bidirectionally polarized, so that F0 is not lowered for the lenis stop. A lack of direct enhancement of the distinctive L tone weakens a possibility that F0 is transphonologized to the phonemic feature system of the language. As an alternative to the view that tonal features are newly introduced in the segmental phonology, we propose a prosodic account: the sound change is best characterized as a prosodically-conditioned change in the use of the segmental voicing feature (implemented by VOT) versus already available post-lexical tones in the intonational phonology of Korean.
Evaluation of Spermatotoxic Effect of Sweet Potato (Ipomoea batatas) Leaf Extract on Male Albino Rats

Aim: The study examined the effect of sweet potato ( Ipomoea batatas ) leaf extract on the sperm toxicity and weight of testes and epididymes in male albino rat models. This study 65 Twenty four male rats were randomly divided into four groups of six rats each using a completely randomized design. Group A served as control and received only water and pellet feed while group B, C and D received 200 mg/kg, 400 mg/kg and 600 mg/kg body weight of the aqueous extract of Ipomoea batatas leaf, respectively. Results: Results obtained revealed a significant ( P = .05) decrease in the weight of epididymes, sperm motility, sperm viability and sperm count while sperm head abnormalities significantly increased in the extract – treated animals. No significant differences were observed in semen pH and weight of testes. Conclusion: The findings of the study suggest that aqueous extract of I. batatas leaf spermatotoxic effect male albino dose – dependent
Icariin-Functionalized Nanodiamonds to Enhance Osteogenic Capacity In Vitro

Nanodiamonds (NDs) have been used as drug delivery vehicles due to their low toxicity and biocompatibility. Recently, it has been reported that NDs have also osteogenic differentiation capacity. However, their capacity using NDs alone is not enough. To significantly improve their osteogenic activity, we developed icariin (ICA)-functionalized NDs (ICA-NDs) and evaluated whether ICA-NDs enhance their in vitro osteogenic capacity. Unmodified NDs and ICA-NDs showed nanosized particles that were spherical in shape. The ICA-NDs achieved a prolonged ICA release for up to 4 weeks. The osteogenic capacities of NDs, ICA (10 μg)-NDs, and ICA (50 μg)-NDs were demonstrated by alkaline phosphatase (ALP) activity; calcium content; and mRNA gene levels of osteogenic-related markers, including ALP, runt-related transcript factor 2 (RUNX2), collagen type I alpha 1 (COL1A1), and osteopontin (OPN). In vitro cell studies revealed that ICA (50 μg)-ND-treated MC3T3-E1 cells greatly increased osteogenic markers, including ALP, calcium content, and mRNA gene levels of osteogenic-related markers, including ALP, RUNX2, COL1A1, and OPN compared to ICA (10 μg)-NDs or ND-treated cells. These our data suggest that ICA-NDs can promote osteogenic capacity.
The role of infarct location in patients with DWI-ASPECTS 0–5 acute stroke treated with thrombectomy

Objective To determine whether hemisphere involvement and infarct location on the Alberta Stroke Program CT Score (ASPECTS) template should serve as predictors of 90-day clinical outcome in patients with acute ischemic stroke with pretreatment diffusion-weighted imaging (DWI)–ASPECTS 0–5 treated with mechanical thrombectomy (MT). Methods We analyzed data of all consecutive patients included in the Endovascular Treatment in Ischemic Stroke registry between January 1, 2012, and August 31, 2018, who presented with a pretreatment DWI-ASPECTS 0–5 and underwent MT. Multivariable analyses were performed in order to identify the role of infarct location and hemisphere involvement on good outcome defined by a modified Rankin Scale (mRS) score 0–2 at 90 days and on the whole distribution of mRS (shift analysis). Results A total of 344 patients with a DWI-ASPECTS 0–5 (median 4, IQR 3–5) were included. Neither infarct location nor hemisphere involvement was found to be an independent predictor of good outcome. Involvement of the M6 region in right-sided strokes (adjusted odds ratio [aOR] 2.6, 99% confidence interval [CI] 1.14–5.8; p = 0.003) and the internal capsule in left-sided strokes (aOR 2.6, 99% CI 0.8–7.9; p < 0.020) independently predicted increased disability on the mRS distribution in the affected subpopulations. Conclusion Our study suggests that neither hemisphere nor infarct location should be considered as an exclusion criterion for MT in patients with stroke with pretreatment DWI-ASPECTS 0–5. The involvement of specific regions of interest was associated with increased disability. These may provide valuable information regarding stroke management options and neurologic recovery for use of caregivers in the postacute phase.
What is Energy Internet? Concepts, Technologies, and Future Directions

The climate change crisis, exacerbated by the global dependency of fossil fuels, has brought significant challenges. In the medium to long term, extensive renewable-energy-based electrification is considered to be one of the most promising development paths to address these challenges. However, this is tangible only if the energy infrastructure can accommodate renewable energy sources and distributed energy resources, such as batteries and heat pumps, without adversely affecting power grid operations. To realize renewable-energy-based electrification goals, a new concept—the Energy Internet (EI)—has been proposed, inspired by the most recent advances in information and telecommunication network technologies. Recently, many measures have also been taken to practically implement the EI. Although these EI models share many ideas, a definitive universal definition of the EI is yet to be agreed. Additionally, some studies have proposed protocols and architectures, but a generalized technological overview is still missing. An understanding of the technologies that underpin and encompass the current and future EI is very important to push toward a standardized version of the EI that will eventually make it easier to implement it across the world. In this paper, we first examine and analyze the typical popular definitions of the EI in scientific literature. Based on definitions, assumptions, scope, and application areas, the scientific literature is then classified into four different groups representing the way in which the papers have approached the EI. Then, we synthesize these definitions and concepts, and keeping in mind the future smart grid, we propose a new universal definition of the EI. We also identify the underlying key technologies for managing, coordinating, and controlling the multiple (distributed or not) subsystems with their own particular challenges. The survey concludes by highlighting the main challenges facing a future EI-based energy system and indicating core requirements in terms of system complexity, security, standardization, energy trading and business models and social acceptance.