Miracle-dz/UniFAR-FTUs huggingface dataset:
Biodegradable silicon nanoneedles for ocular drug delivery

Ocular drug delivery remains a grand challenge due to the complex structure of the eye. Here, we introduce a unique platform of ocular drug delivery through the integration of silicon nanoneedles with a tear-soluble contact lens. The silicon nanoneedles can penetrate into the cornea in a minimally invasive manner and then undergo gradual degradation over the course of months, enabling painless and long-term sustained delivery of ocular drugs. The tear-soluble contact lens can fit a variety of corneal sizes and then quickly dissolve in tear fluid within a minute, enabling an initial burst release of anti-inflammatory drugs. We demonstrated the utility of this platform in effectively treating a chronic ocular disease, such as corneal neovascularization, in a rabbit model without showing a notable side effect over current standard therapies. This platform could also be useful in treating other chronic ocular diseases.
Ten years of riluzole use in a tertiary ALS clinic

Riluzole is a glutamate inhibitor approved for the treatment of amyotrophic lateral sclerosis (ALS). There are scant data on factors associated with riluzole initiation and adherence. The goal of this study was to describe the use of riluzole at the Penn State Hershey Medical Center (PSHMC) ALS clinic.
Healthy and unhealthy eating after a behaviour change intervention in primary care

Abstract Background: To prevent and reduce non-communicable diseases, the Norwegian Directorate of Health encourages Healthy Life Centres (HLCs) in all municipalities. Aims: This study investigates whether the behaviour change interventions at HLCs positively affected participants’ diet and to evaluate predictors for healthy and unhealthy eating. Our data are part of the Norwegian Healthy Life Centre Study, a 6-month, pragmatic randomised controlled trial (RCT). Methods: Totally, 118 participants ≥18 years old were randomised to an intervention group (n 57), or a waiting list (control group) (n 61). Eighty-six participants met at the 6 months follow-up visit. We merged the participants to one cohort for predictor analyses, using linear regressions. Findings: The RCT of the HLCs’ interventions had no effect on healthy and unhealthy eating 6 months after baseline compared with controls. A short, additional healthy eating education programme produced a modest, statistically significant improvement in healthy eating compared with controls. This did not, however, reduce unhealthy eating. Higher income predicted unhealthier eating over time. Increasing body mass index and impaired physical functioning also led to an increase in unhealthy eating. Healthy eating at 6 months was predicted by self-rated health (SRH), vitality and life satisfaction, and hampered by musculo-skeletal challenges and impaired self-esteem (SE). SRH impacted improvement in healthy eating during the 6 months. The effect of interventions on healthier eating may be improved by an emphasis on developing positive self-concepts like better SRH, vitality, life satisfaction, and SE.
Enhancing cavitation dynamics and its mechanical effects with dual-frequency ultrasound

Objective. Acoustic cavitation and its mechanical effects (e.g. stress and strain) play a primary role in ultrasound applications. Introducing encapsulated microbubbles as cavitation nuclei and utilizing dual-frequency ultrasound excitation are highly effective approaches to reduce cavitation thresholds and enhance cavitation effects. However, the cavitation dynamics of encapsulated microbubbles and the resultant stress/strain in viscoelastic tissues under dual-frequency excitation are poorly understood, especially for the enhancement effects caused by a dual-frequency approach. The goal of this study was to numerically investigate the dynamics of a lipid-coated microbubble and the spatiotemporal distributions of the stress and strain under dual-frequency excitation. Approach. The Gilmore–Zener bubble model was coupled with a shell model for the nonlinear changes of both shell elasticity and viscosity to accurately simulate the cavitation dynamics of lipid-coated microbubbles in viscoelastic tissues. Then, the spatiotemporal evolutions of the cavitation-induced stress and strain in the surrounding tissues were characterized quantitatively. Finally, the influences of some paramount parameters were examined to optimize the outcomes. Main results. We demonstrated that the cavitation dynamics and associated stress/strain were prominently enhanced by a dual-frequency excitation, highlighting positive correlations between the maximum bubble expansion and the maximum stress/strain. Moreover, the results showed that the dual-frequency ultrasound with smaller differences in its frequencies and pressure amplitudes could enhance the bubble oscillations and stress/strain more efficiently, whereas the phase difference manifested small influences under these conditions. Additionally, the dual-frequency approach seemed to show a stronger enhancement effect with the shell/tissue viscoelasticity increasing to a certain extent. Significance. This study might contribute to optimizing the dual-frequency operation in terms of cavitation dynamics and its mechanical effects for high-efficient ultrasound applications.
A Novel Resource Sharing Scheme for Full Duplex D2D Communication Underlaying Cellular Network

In this paper, we propose a novel resource sharing scheme for full duplex device-to-device (D2D) communication underlaying cellular network. In the considered scenario, two D2D users share the downlink spectrum resource with two cellular users. When the two D2D users transmit signals to each other, they also act as relays between the base station (BS) and the cellular users so that the cellular users can leverage the redundant capacity of the two full duplex D2D users. To optimize the performance of the scheme, the power allocation is optimized by considering the impact of residual self-interference at full duplex radios and the quality of services (QoS) requirement for both cellular users and D2D users. The simulation results show that, compared to the existing research scheme, the proposed scheme can achieve larger sum channel capacity for the transmission of cellular users, and it can also achieve larger average system throughput at high signal to interference plus noise ratio (SINR) region.
KL-Mat: Fair Recommender System via Information Geometry

Recommender system has intrinsic problems such as sparsity and fairness. Although it has been widely adopted for the past decades, research on fairness of recommendation algorithms has been largely neglected until recently. One important paradigm for resolving the issue is regularization. However, researchers have not been able to come up with a consensusly agreed regularization term like regularization framework in other fields such as Lasso or Ridge Regression. In this paper, we borrow concepts from information geometry and propose a new regularization-based fair algorithm called KL-Mat. The algorithmic technique leads to a more robust performance in accuracy performance such as MAE. More importantly, the algorithm produces much fairer results than vanilla matrix factorization approach. KL-Mat is fast, easy-to-implement and explainable.
Low-cost phantoms for validating measurements in ultrasound vascular images

Ultrasound is widely used as an inexpensive, real-time method for imaging vascular tissue. However, sonographs often lack automatic or semi-automatic software for measuring vascular diameter precisely, especially in low- and mid-income countries or institutions. Tools can be developed to perform this task, but they must be validated before being accepted for clinic use. For that purpose, in this work we present low-cost phantoms that resemble vascular tissue when subjected to ultrasound. Several materials are analysed and a step-by-step recipe for building a simple phantom is presented. Qualitatively, models were imaged by an ultrasound expert physician, and several characteristic are assessed. Quantitatively, a comparison between ultrasound and caliper measurements of the phantoms is presented. Finally, a discussion about the results and the recommended materials for low-cost vascular phantoms is carried out.
Hyper-dimensional Visualization of Cultural Heritage: A Novel Multi-analytical Approach on 3D Pomological Models in the Collection of the University of Milan

Digital close-range photogrammetry allows us to acquire high-fidelity tridimensional models useful to document cultural heritage objects with an impressive level of detail. In addition, this technique carries a strong analytical potentiality, able to gain improved knowledge of cultural objects and their preservation conditions. This project is focused on a comprehensive diagnostic survey using 3D multispectral modeling, high-resolution digital radiography, pulsed thermography, XRF, FT-IR, and FORS spectroscopies to document and characterize from a conservative point of view the poly-material objects that belong to the “Garnier Valletti” pomological collection—a unique collection from both scientific and artistic points of view. The analytical integration of imaging techniques, 3D modeling, and spectroscopic techniques provides information from the surface, sub-surface, and innermost layers of the object, respectively, capturing both accurate morphometric, spectral, and compositional data. The article presents the results obtained on typical poly-material and multilayered objects of this collection for which the combination of the considered techniques provided important data to the technical knowledge of the realization highlighting a particular predictive ability from a conservative point of view.
MUA-Router: Maximizing the Utility-of-Allocation for On-chip Pipelining Routers

As an important pipeline stage in the router of Network-on-Chips, switch allocation assigns output ports to input ports and allows flits to transit through the switch without conflicts. Previous work designed efficient switch allocation strategies by maximizing the matching efficiency in time series. However, those works neglected the interaction between different router pipeline stages. In this article, we propose the concept of Utility-of-Allocation (UoA) to indicate the quality of allocation to be practically used in on-chip routers. We demonstrate that router pipelines can interact with each other, and the UoA can be maximized if the interaction between router pipelines is taken into consideration. Based on these observations, a novel class of routers, MUA-Router, is proposed to maximize the UoA through the collaborative design (co-design) between router pipelines. MUA-Router achieves this goal in two ways and accordingly implements two novel instance router architectures. In the first, MUA-Router improves the UoA by mitigating the impact of endpoint congestion in the switch allocation, and thus Eca-Router is proposed. Eca-Router achieves an endpoint-congestion-aware switch allocation through the co-design between routing computation and switch allocation. Based on Eca-Router, CoD-Router is proposed to feed back switch allocation information to routing computation stage to provide switch allocator with more conflict-free requests. Through the co-design between pipelines, MUA-Router significantly improves the efficiency of switch allocation and the performance of the entire network. Evaluation results show that our design can achieve significant performance improvement with moderate overheads.
Complete nutrition drink with retrograded starch is low glycemic, and the individual glucose response to the low glycemic complete nutrition drink depends on fasting insulin levels and HOMA-IR in a randomized cross-over control trial

Abstract Complete nutrition drinks with a low glycemic index (GI) provide nutritional support and prevent hyperglycaemia. The present study identified GI and factors predicting individual glucose response to a new complete nutrition drink. A randomised cross-over controlled trial was conducted in eighteen healthy volunteers (FPG < 100 mg/dl). Complete nutrition drinks containing retrograded starch, glucose solution and white bread were assigned in a random sequence with 14-day wash-out intervals. Plasma glucose and insulin levels were measured from baseline to 180 min after consuming each food. Results show the adjusted GIs of the drink was 48.2 ± 10.4 and 46.7 ± 12.7 with glucose and white bread as the reference, respectively. While the drink has low GI (<55), the individual glucose responses varied (GI: 7–149). Comparing characters in individual GI < 55 (n = 12) and GI ≥ 55 (n = 6) groups revealed significantly higher baseline insulin in the low GI group (14.86 ± 16.51 μIU/ml v. 4.9 ± 3.4 μIU/ml, P < 0·05). The correlation matrix confirms only two predictive factors for having individual GI <55 were baseline insulin (r = 0·5, P = 0·03) and HOMA-IR (r = 0·55, P = 0·02). ROC curve reveals fasting insulin above 1.6 μIU/ml and HOMA-IR above 1.05 as the cut-off values. The findings suggest that the complete nutrition drink has a low GI, but there was wide variability in individual responses partly explained by fasting insulin levels and HOMA-IR. Screening for fasting insulin and HOMA-IR may be encouraged to maximise the functional benefit of the drink.
Cultural adaptation of cognitive behaviour therapy for depression: a qualitative study exploring views of patients and practitioners from India

Abstract Cognitive behaviour therapy (CBT) is an effective treatment for depression. However, culture can influence engagement and treatment efficacy of CBT. Several attempts have been made in Asian countries to develop a culturally adapted CBT for depression. However, research in the Indian context documenting the views on cultural influence of CBT is limited. The present study is an attempt to explore the views of patients and therapists in India by following an evidence-based approach that focuses on three areas for adaptation: (1) awareness of relevant cultural issues and preparation for therapy; (2) assessment and engagement; and (3) adjustments in therapy techniques. Semi-structured interviews with three consultant clinical psychologists/therapists, a focused group discussion with six clinical psychologists, and two patients undergoing CBT for depression were conducted. The data were analysed using a thematic framework analysis by identifying emerging themes and categories. The results highlight therapists’ experiences, problems faced, and recommendations in all three areas of adaptation. The findings highlight the need for adaptation with understanding and acknowledging the culture differences and clinical presentation. Culturally sensitive assessment and formulation with minor adaptation in clinical practice was recommended. Therapists emphasised the use of proverbs, local stories and simplified terminologies in therapy. The findings will aid in providing culturally sensitive treatment to patients with depression in India. Key learning aims (1) To understand the views of Indian patients and therapists based on their experience of CBT. (2) To understand the need for cultural adaptation of CBT in India. (3) To understand the adaptations by therapists while using CBT in clinical practice. (4) To gain perspective on how CBT can be culturally adapted to meet the needs of the Indian population.
Adaptive Power Management for Autonomic Resource Configuration in Large-scale Computer Systems

In order to run and manage resource-intensive high-performance applications, large-scale computing and storage platforms have been evolving rapidly in various domains in both academia and industry. The energy expenditure consumed to operate and maintain these cloud computing infrastructures is a major factor to influence the overall profit and efficiency for most cloud service providers. Moreover, considering the mitigation of environmental damage from excessive carbon dioxide emission, the amount of power consumed by enterprise-scale data centers should be constrained for protection of the environment.Generally speaking, there exists a trade-off between power consumption and application performance in large-scale computing systems and how to balance these two factors has become an important topic for researchers and engineers in cloud and HPC communities. Therefore, minimizing the power usage while satisfying the Service Level Agreements have become one of the most desirable objectives in cloud computing research and implementation. Since the fundamental feature of the cloud computing platform is hosting workloads with a variety of characteristics in a consolidated and on-demand manner, it is demanding to explore the inherent relationship between power usage and machine configurations. Subsequently, with an understanding of these inherent relationships, researchers are able to develop effective power management policies to optimize productivity by balancing power usage and system performance. In this dissertation, we develop an autonomic power-aware system management framework for large-scale computer systems. We propose a series of techniques including coarse-grain power profiling, VM power modelling, power-aware resource auto-configuration and full-system power usage simulator. These techniques help us to understand the characteristics of power consumption of various system components. Based on these techniques, we are able to test various job scheduling strategies and develop resource management approaches to enhance the systems' power efficiency.
Evaluation of The Probiotic Potential of Lactobacillus Delbrueckii Ssp. indicus WDS-7 Isolated from Chinese Traditional Fermented Buffalo Milk In Vitro

Abstract The present study aimed to evaluate the probiotic potential of lactic acid bacteria (LAB) isolated from Chinese traditional fermented buffalo milk. Out of 22 isolates, 11 were putatively identified as LAB preliminarily. A total of six LAB strains displayed strong adhesion to HT-29 cells and all these strains showed preferable tolerance to artificially simulated gastrointestinal juices. WDS-4, WDS-7, and WDS-18 exhibited excellent antioxidant capacities, including DPPH radical, ABTS+ radical, and superoxide anion scavenging activities. Compared with the other two LAB strains, WDS-7 had a stronger inhibition effect on four pathogens. Based on the 16S rRNA gene sequencing and phylogenetic analysis, WDS-7 was identified as Lactobacillus delbrueckii ssp. indicus and selected to assess the potential and safety of probiotics further. The results revealed that WDS-7 strain had a strong capacity for acid production and good thermal stability. WDS-7 strain also possessed bile salt hydrolase (BSH) activity. Compared to LGG, WDS-7 was a greater biofilm producer on the plastic surface and exhibited a better EPS production ability (1.94 mg/ml as a glucose equivalent). WDS-7 was proved to be sensitive in the majority of tested antibiotics and absence of hemolytic activity. Moreover, no production of biogenic amines and β-glucuronidase was observed in WDS-7. The findings of this work indicated that L. delbrueckii ssp. indicus WDS-7 fulfilled the probiotic criteria in vitro and could be exploited for further evaluation in vivo.
IoT DEVELOPMENT FOR HEALTHY INDEPENDENT LIVING

OF THESIS IoT DEVELOPMENT FOR HEALTHY INDEPENDENT LIVING The rise of internet connected devices has enabled the home with a vast amount of enhancements to make life more convenient. These internet connected devices can be used to form a community of devices known as the internet of things (IoT). There is great value in IoT devices to promote healthy independent living for older adults. Fall-related injuries has been one of the leading causes of death in older adults. For example, every year more than a third of people over 65 in the U.S. experience a fall, of which up to 30 percent result in moderate to severe injury. Therefore, this thesis proposes an IoT-based fall detection system for smart home environments that not only to send out alerts, but also launches interaction models, such as voice assistance and camera monitoring. Such connectivity could allow older adults to interact with the system without concern of a learning curve. The proposed IoT-based fall detection system will enable family and caregivers to be immediately notified of the event and remotely monitor the individual. Integrated within a smart home environment, the proposed IoT-based fall detection system can improve the quality of life among older adults. Along with the physical concerns of health, psychological stress is also a great concern among older adults. Stress has been linked to emotional and physical conditions such as depression, anxiety, heart attacks, stroke, etc. Increased susceptibility to stress may accelerate cognitive decline resulting in conversion of cognitively normal older adults to MCI (Mild Cognitive Impairment), and MCI to dementia. Thus, if stress can be measured, there can be countermeasures put in place to reduce stress and its negative effects on the psychological and physical health of older adults. This thesis presents a framework that can be used to collect and pre-process physiological data for the purpose of validating galvanic skin response (GSR), heart rate (HR), and emotional valence (EV) measurements against the cortisol and self-reporting benchmarks for stress detection. The results of this framework can be used for feature extraction to feed into a regression model for validating each combination of physiological measurement. Also, the potential of this framework to automate stress protocols like the Trier Social Stress Test (TSST) could pave the way for an IoT-based platform for automated stress detection and management.