Miracle-dz/UniFAR-FTUs huggingface dataset:
Social robotics to support older people with dementia: a study protocol with Paro seal robot in an Italian Alzheimer’s day center

Introduction The aging of the population and the high incidence of those over 80 lead to an inevitable increase in chronic degenerative diseases, such as dementia, resulting in increased morbidity and disability. Treatment of people with dementia involves both pharmacological and non-pharmacological interventions. In particular, robot-assisted therapy is a potentially useful treatment for dementia as it has the advantage of improving mood, encouraging social interaction and communication. The overall objective of the study is to evaluate the improvement in patient-perceived quality of life following the use of the Paro robot integrated with usual care in the older people with dementia. Methods and analysis For this study, 20 patients with dementia are recruited and divided into Experimental Group (EG) and Control Group (CG). Twenty-four session of intervention are conducted, divided into 2 sessions per week, for 12 weeks. The therapy sessions last 20 min. The Experimental Group will receive a social robotic intervention with Paro combined with usual care; the Control Group will receive only the traditional therapy, consisting of cognitive stimulation (reality orientation therapy, cognitive training) and occupational activities (painting workshops, cooking workshops, garden therapy, music therapy, etc.). Paro is a seal-shaped robot designed to have a calming effect and elicit emotional responses in patients in hospitals, nursing homes, and retirement homes. Assessment will be performed at the baseline, at the end of intervention and 3 months after the end of intervention. During these phases, several scales will be administered to the patients, such as Quality of Life—Alzheimer’s Disease, Addenbrooke’s Cognitive Examination, the Rating Anxiety In Dementia scale and the Cornell Scale for Depression in Dementia, Quebec User Evaluation of Satisfaction, Neuropsychiatric Inventory, the Technology Acceptance Model. Discussions The final goals of the present study are to evaluate the improvement in patient-perceived quality of life following the use of the Paro robot integrated with usual care in the older people with dementia. Ethics and dissemination The study was approved by the Ethic Committee of the Istituto Nazionale Ricovero e Cura Anziani, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS INRCA) during the session of 12 April 2022. It was recorded in ClinicalTrials.gov on 23 November 2022 on the number NCT05626205. The study findings will be used for publication in peer-reviewed scientific journals and presentations in scientific meetings.
Pipeline Leak Audio Detection System based on Machine Learning

It is of great practical significance to study intelligent robots for crack detection of urban underground pipes instead of manual detection, which not only can save time and cost, but also can improve the accuracy rate of identification. The system consists of two parts: mobile platform and system detection platform. The mobile platform is obstacle-avoiding by ultrasonic module, segmenting the pipeline color by camera and issuing platform steering command. The system detection platform adopts Raspberry Pi as the core control system, and collects the pipeline leakage audio through the pickups, and the collected audio is passed through Gaussian mixture model-Hidden Markov model (GMM -HMM) and Deep neural networks- Hidden Markov model (DNN -HMM) respectively in Raspberry Pi model (DNN -HMM) for the purpose of detection. The accuracy and running speed of the two methods were tested separately through simulation experiments. GMM -HMM achieves 74.1% accuracy and 14 (frame/s) running speed, while DNN -HMM achieves 80.6% accuracy and 9 (frame/s) running speed, DNN -HMM has higher accuracy and running speed to meet the real-time requirements for pipeline leakage audio detection.
Lightweight Register File Caching in Collector Units for GPUs

Modern GPUs benefit from a sizable Register File (RF) to provide fine-grained thread switching. As the RF is huge and accessed frequently, it consumes a considerable share of the dynamic energy of the GPU. Designing a large, high-throughput RF with low energy consumption and area for GPUs is challenging. In this paper, an energy-efficient hierarchical RF design for GPUs, called Malekeh, is introduced. Malekeh keeps registers in energy-efficient small caches and maximizes cache efficacy by using lightweight policies and supporting adaptive algorithms. The policies’ effectiveness is improved by leveraging register reuse distance information provided by the compiler as a hint. Malekeh reduces the RF reads by 48.5% and dynamic energy by 29.1%. It also improves performance by 9.6% with a negligible overhead of 0.04% in area.
Investigating chemical, antioxidant, and sensory properties of chocolate fortified with cactus stems powder

Objective The present study aimed to examine the sensory, antioxidant, and chemical characteristics of chocolate that were enhanced with a powder derived from cactus leaves. Methods Treatments were prepared by fortified chocolate with cactus stems powder at different levels (0%, 3%, 5%, and 7%) w/w. Results The results indicated that fortification of chocolate with cactus stems powder increased significantly (p ≤ 0.05) moisture, protein, ash, total carbohydrate, and fiber of chocolate treatments with cactus stems powder, in comparison to the control group (0%). On the contrary, there was a notable (p ≤ 0.05) reduction in fat content in all the treatments that contained cactus leaf powder. Conclusions The augmentation of cactus stems powder in chocolate treatments had a positive impact on their antioxidant activity, which increased with increasing the concentration of the powder. In addition, this inclusion of cactus stems powder aided in lowering the oxidative degradation of the chocolate treatments. The sensory analysis findings revealed no significant difference between mean ratings for the overall acceptability of control chocolate and fortified chocolate treatments (p ≤ 0.05).
Scalable algorithms for compact spanners on real world graphs

A graph spanner is a subgraph that preserves the shortest distance between every pair of vertices within a permissible distortion. Typically, the allowed distortion is a multiplicative factor (of the original distances) and is referred to as stretch. Efficient multiplicative spanners, based on finding low diameter decompositions, have been studied in the distributed and parallel settings. Most of these studies aim to find spanners with theoretical guarantees on the stretch and spanner size. The spanner size guarantees obtained in these works are not very useful for real world sparse graphs. In this work, we evaluate and compare the state of the art algorithms for multiplicative spanners on real world and synthetic graphs. We propose a heuristic that aims to reduce the size of the output spanner. When combined with existing approaches, it admits similar theoretical guarantees as described in prior work while yielding considerably smaller spanners. Our heuristic builds on the idea of selecting centers with large neighborhoods and growing clusters around them. We present a parallel algorithm for selecting a large set of cluster centers based on this heuristic. We evaluate our algorithms on 18 real world graphs from the SNAP data set and 3 well studied synthetic graphs. We demonstrate that our heuristic yields spanners with significantly fewer edges - up to 6x smaller on real world graphs and up to 20x smaller on synthetic graphs, compared to baselines from prior work.
SAELGMDA: Identifying human microbe–disease associations based on sparse autoencoder and LightGBM

Introduction Identification of complex associations between diseases and microbes is important to understand the pathogenesis of diseases and design therapeutic strategies. Biomedical experiment-based Microbe-Disease Association (MDA) detection methods are expensive, time-consuming, and laborious. Methods Here, we developed a computational method called SAELGMDA for potential MDA prediction. First, microbe similarity and disease similarity are computed by integrating their functional similarity and Gaussian interaction profile kernel similarity. Second, one microbe-disease pair is presented as a feature vector by combining the microbe and disease similarity matrices. Next, the obtained feature vectors are mapped to a low-dimensional space based on a Sparse AutoEncoder. Finally, unknown microbe-disease pairs are classified based on Light Gradient boosting machine. Results The proposed SAELGMDA method was compared with four state-of-the-art MDA methods (MNNMDA, GATMDA, NTSHMDA, and LRLSHMDA) under five-fold cross validations on diseases, microbes, and microbe-disease pairs on the HMDAD and Disbiome databases. The results show that SAELGMDA computed the best accuracy, Matthews correlation coefficient, AUC, and AUPR under the majority of conditions, outperforming the other four MDA prediction models. In particular, SAELGMDA obtained the best AUCs of 0.8358 and 0.9301 under cross validation on diseases, 0.9838 and 0.9293 under cross validation on microbes, and 0.9857 and 0.9358 under cross validation on microbe-disease pairs on the HMDAD and Disbiome databases. Colorectal cancer, inflammatory bowel disease, and lung cancer are diseases that severely threat human health. We used the proposed SAELGMDA method to find possible microbes for the three diseases. The results demonstrate that there are potential associations between Clostridium coccoides and colorectal cancer and one between Sphingomonadaceae and inflammatory bowel disease. In addition, Veillonella may associate with autism. The inferred MDAs need further validation. Conclusion We anticipate that the proposed SAELGMDA method contributes to the identification of new MDAs.
Temporal and spatial changes in rhizosphere bacterial diversity of mountain Rhododendron mucronulatum

To better conserve the ecology of the wild Rhododendron mucronulatum range, we studied the rhizosphere microenvironment of R. mucronulatum in Beijing’s Yunmeng Mountain National Forest Park. R. mucronulatum rhizosphere soil physicochemical properties and enzyme activities changed significantly with temporal and elevational gradients. The correlations between soil water content (SWC), electrical conductivity (EC), organic matter content (OM), total nitrogen content (TN), catalase activity (CAT), sucrose-converting enzyme activity (INV), and urease activity (URE) were significant and positive in the flowering and deciduous periods. The alpha diversity of the rhizosphere bacterial community was significantly higher in the flowering period than in the deciduous period, and the effect of elevation was insignificant. The diversity of the R. mucronulatum rhizosphere bacterial community changed significantly with the change in the growing period. A network analysis of the correlations revealed stronger linkages between the rhizosphere bacterial communities in the deciduous period than in the flowering period. Rhizomicrobium was the dominant genus in both periods, but its relative abundance decreased in the deciduous period. Changes in the relative abundance of Rhizomicrobium may be the main factor influencing the changes in the R. mucronulatum rhizosphere bacterial community. Moreover, the R. mucronulatum rhizosphere bacterial community and soil characteristics were significantly correlated. Additionally, the influence of soil physicochemical properties on the rhizosphere bacterial community was larger than that of enzyme activity on the bacterial community. We mainly analyzed the change patterns in the rhizosphere soil properties and rhizosphere bacterial diversity of R. mucronulatum during temporal and spatial variation, laying the foundation for further understanding of the ecology of wild R. mucronulatum.
HARQ Retransmission Design for SC-LDPC Codes

In channel coding, spatially coupled low density parity check (SC-LDPC) codes can approach the Shannon limit theoretically because of its ”threshold saturation” characteristic. Compared with LDPC code, SC-LDPC code with spatial coupling structure can bring higher performance gain and is more suitable for streaming data transmission system. However, with the increasing demand for the reliability of communication systems, how to construct sc-ldpc codes that meet the performance requirements has become the focus of research. This paper mainly studies the construction method of SC-LDPC code based on LDPC code check matrix, in order to further improve the system reliability. Based on this, a construction scheme of sc-ldpc code with code rate compatible is proposed. In order to further verify the feasibility of sc-ldpc code application, the code rate compatible SC-LDPC code is applied to hybrid automatic repeat request (HARQ) technology, and a HARQ retransmission technology scheme with code rate compatible SC-LDPC code is designed.
Energy Efficient Offloading Strategy faced to Edge Computing-enhanced Distributed Photovoltaic Smart Meter

With the rapid development of Power Internet of Things and the increase in the number of distributed photovoltaic smart meter (DPSM) technology, edge computing is required to support the low-latency computing service. Current works mainly focus on task offloading, the cooperation among smart meter devices is lack of attention. In order to reduce the task execution delay in of the network, a computing resource sharing architecture based on D2D is proposed. In order to reduce the processing delay and energy consumption of DPSM, we propose a task offloading model faced to DPSM. To minimize the total task execution delay, we formulate a Mixed-Integer Non-Linear Programming (MINLP) problem which optimizing task offloading and resource allocation jointly. Then, a generalized Benders decomposition algorithm combined with particle swarm optimization is proposed to solve the problem. Simulation results show that the proposed strategy can effectively improve the measurement efficiency and reduce the computational cost.
Modifications in cellular viability, DNA damage and stress responses inflicted in cancer cells by copper-64 ions

Due to combined therapeutical emissions, a high linear energy transfer Auger-electrons with the longer ranged β− particles, 64Cu-based radiopharmaceuticals raise particular theragnostic interest in cancer, by joined therapeutic and real-time PET imaging properties. The in vitro study aimed to investigate the biological and molecular background of 64CuCl2 therapy by analyzing the damages and stress responses inflicted in various human normal and tumor cell lines. Colon (HT29 and HCT116) and prostate carcinoma (DU145) cell lines, as well as human normal BJ fibroblasts, were treated up to 72 h with 2–40 MBq/mL 64CuCl2. Radioisotope uptake and retention were assessed, and cell viability/death, DNA damage, oxidative stress, and the expression of 84 stress genes were investigated at various time points after [64Cu]CuCl2 addition. All the investigated cells incorporated 64Cu ions similarly, independent of their tumoral or normal status, but their fate after exposure to [64Cu]CuCl2 was cell-dependent. The most striking cytotoxic effects of the radioisotope were registered in colon carcinoma HCT116 cells, for which a substantial decrease in the number of metabolically active cells, and an increased DNA damage and oxidative stress were registered. The stress gene expression study highlighted the activation of both death and repair mechanisms in these cells, related to extrinsic apoptosis, necrosis/necroptosis or autophagy, and cell cycle arrest, nucleotide excision repair, antioxidant, and hypoxic responses, respectively. The in vitro study indicated that 40 MBq/mL [64Cu]CuCl2 delivers a therapeutic effect in human colon carcinoma, but its use is limited by harmful, yet lower effects on normal fibroblasts. The exposure of tumor cells to 20 MBq/mL [64Cu]CuCl2, might be used for a softer approach aiming for a lower radiotoxicity in normal fibroblasts as compared to tumor cells. This radioactive concentration was able to induce a persistent decrease in the number of metabolically active cells, accompanied by DNA damage and oxidative stress, associated with significant changes in stress gene expression in HCT116 colon cancer cells.
Alternative patterns of deep brain stimulation in neurologic and neuropsychiatric disorders

Deep brain stimulation (DBS) is a widely used clinical therapy that modulates neuronal firing in subcortical structures, eliciting downstream network effects. Its effectiveness is determined by electrode geometry and location as well as adjustable stimulation parameters including pulse width, interstimulus interval, frequency, and amplitude. These parameters are often determined empirically during clinical or intraoperative programming and can be altered to an almost unlimited number of combinations. Conventional high-frequency stimulation uses a continuous high-frequency square-wave pulse (typically 130–160 Hz), but other stimulation patterns may prove efficacious, such as continuous or bursting theta-frequencies, variable frequencies, and coordinated reset stimulation. Here we summarize the current landscape and potential clinical applications for novel stimulation patterns.
Cognitive and affective interaction with somatosensory afference in acupuncture–a specific brain response to compound stimulus

Introduction Acupuncture is a clinical intervention consisting of multiple stimulus components, including somatosensory stimulation and manipulation of therapeutic context. Existing findings in neuroscience consolidated cognitive modulation to somatosensory afferent process, which could differ from placebo mechanism in brain. Here, we aimed to identify intrinsic process of brain interactions induced by compound stimulus of acupuncture treatment. Methods To separately and comprehensively investigate somatosensory afferent and cognitive/affective processes in brain, we implemented a novel experimental protocol of contextual manipulation with somatosensory stimulation (real acupuncture: REAL) and only contextual manipulation (phantom acupuncture: PHNT) for fMRI scan, and conducted independent component (IC)-wise assessment with the concatenated fMRI data. Results By our double (experimentally and analytically) dissociation, two ICs (CA1: executive control, CA2: goal-directed sensory process) for cognitive/affective modulation (associated with both REAL and PHNT) and other two ICs (SA1: interoceptive attention and motor-reaction, SA2: somatosensory representation) for somatosensory afference (associated with only REAL) were identified. Moreover, coupling between SA1 and SA2 was associated with a decreased heart rate during stimulation, whereas CA1 was associated with a delayed heart rate decrease post-stimulation. Furthermore, partial correlation network for these components demonstrated a bi-directional interaction between CA1 and SA1/SA2, suggesting the cognitive modulation to somatosensory process. The expectation for the treatment negatively affected CA1 but positively affected SA1 in REAL, whereas the expectation positively affected CA1 in PHNT. Discussion These specific cognitive-somatosensory interaction in REAL were differed from vicarious sensation mechanism in PHNT; and might be associated with a characteristic of acupuncture, which induces voluntary attention for interoception. Our findings on brain interactions in acupuncture treatment elucidated the underlying brain mechanisms for compound stimulus of somatosensory afferent and therapeutic contextual manipulation, which might be a specific response to acupuncture.
Antithrombotic therapy in antiphospholipid syndrome with arterial thrombosis: a systematic review and network meta-analysis

Introduction The optimal secondary thromboprophylactic strategies for patients with antiphospholipid syndrome (APS) and arterial thrombosis remain controversial. This study aimed to evaluate the comparative efficacy and safety of various antithrombotic strategies in APS with arterial thrombosis. Methods A comprehensive literature search was conducted using OVID MEDLINE, EMBASE, Web of Science, and the Cochrane Controlled Register of Trials (CENTRAL) from inception until 30 September 2022, with no language restrictions. The inclusion criteria for eligible studies were as follows: inclusion of APS patients with arterial thrombosis, treatment with either antiplatelet agents, warfarin, direct oral anticoagulants (DOACs), or a combination of these therapies, and reporting of recurrent thrombotic events. Results We conducted a frequentist random-effects network meta-analysis (NMA) involving 13 studies with a total of 719 participants, comprising six randomized and seven non-randomized studies. In comparison to single antiplatelet therapy (SAPT), the combined use of antiplatelet and warfarin demonstrated a significant reduction in the risk of recurrent overall thrombosis, with a risk ratio (RR) of 0.41 (95% CI 0.20 to 0.85). Dual antiplatelet therapy (DAPT) showed a lower risk of recurrent arterial thrombosis compared to SAPT although the difference did not reach statistical significance, with an RR of 0.29 (95% CI 0.08 to 1.07). DOAC was associated with a significant increase in the risk of recurrent arterial thrombosis, with an RR of 4.06 (95% CI 1.33 to 12.40) when compared to SAPT. There was no significant difference in major bleeding among various antithrombotic strategies. Discussion Based on this NMA, the combination of warfarin and antiplatelet therapy appears to be an effective approach in preventing recurrent overall thrombosis in APS patients with a history of arterial thrombosis. While DAPT may also show promise in preventing recurrent arterial thrombosis, further studies are needed to confirm its efficacy. Conversely, the use of DOACs was found to significantly increase the risk of recurrent arterial thrombosis.
Internalizing and externalizing symptoms in children during the COVID-19 pandemic: a systematic mixed studies review

Introduction Given the vulnerability of children during the COVID-19 pandemic, paying close attention to their wellbeing at the time is warranted. The present protocol-based systematic mixed-studies review examines papers published during 2020–2022, focusing on the impact of the COVID-19 pandemic on children's internalizing/externalizing symptoms and the determinants thereof. Method PROSPERO: CRD42022385284. Five databases were searched and the PRISMA diagram was applied. The inclusion criteria were: papers published in English in peer-reviewed journals; papers published between January 2020 and October 2022 involving children aged 5–13 years; qualitative, quantitative, and mixed studies. The standardized Mixed Method Appraisal Tool protocol was used to appraise the quality of the studies. Results Thirty-four studies involving 40,976 participants in total were analyzed. Their principal characteristics were tabulated. The results showed that children's internalizing/externalizing symptoms increased during the pandemic, largely as a result of disengagement from play activities and excessive use of the internet. Girls showed more internalizing symptoms and boys more externalizing symptoms. Distress was the strongest parental factor mediating children's internalizing/externalizing symptoms. The quality of the studies was appraised as low (n = 12), medium (n = 12), and high (n = 10). Conclusion Gender-based interventions should be designed for children and parents. The studies reviewed were cross-sectional, so long-term patterns and outcomes could not be predicted. Future researchers might consider a longitudinal approach to determine the long-term effects of the pandemic on children's internalizing and externalizing symptoms. Systematic review registration https://www.crd. york.ac. uk/prospero/display_record. php? ID=CRD42022385284, identifier: CRD42022385284.