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It is found that nodes in Delay Tolerant Networks (DTN) exhibit stable social attributes similar to those of people. In this paper, an adaptive routing algorithm based on Relation Tree (AR-RT) for DTN is proposed. Each node constructs its own Relation Tree based on the historical encounter frequency, and will adopt different forwarding strategies based on the Relation Tree in the forwarding phase, so as to achieve more targeted forwarding. To further improve the scalability of the algorithm, the source node dynamically controls the initial maximum number of message copies according to its own cache occupancy, which enables the node to make negative feedback to network environment changes. Simulation results show that the AR-RT algorithm proposed in this paper has significant advantages over existing routing algorithms in terms of average delay, average hop count, and message delivery rate.

People with sleep apnea (SA) are at increased risk of having stroke and cardiovascular diseases. Polysomnography (PSG) is used to detect SA. This paper conducts feature selection from PSG signals and uses a support vector machine (SVM) to detect SA. To analyze SA, the Physionet Apnea Database was used to obtain various features. Electrocardiography (ECG), oxygen saturation (SaO2), airflow, abdominal, and thoracic signals were used to provide various frequency-, time-domain and non-linear features (n = 87). To analyse the significance of these features, firstly, two evaluation measures, the rank-sum method and the analysis of variance (ANOVA) were used to evaluate the significance of the features. These features were then classified according to their significance. Finally, different class feature sets were presented as inputs for an SVM classifier to detect the onset of SA. The hill-climbing feature selection algorithm and the k-fold cross-validation method were applied to evaluate each classification performance. Through the experiments, we discovered that the best feature set (including the top-five significant features) obtained the best classification performance. Furthermore, we plotted receiver operating characteristic (ROC) curves to examine the performance of the SVM, and the results showed the SVM with Linear kernel (regularization parameter = 1) outperformed other classifiers (area under curve = 95.23%, sensitivity = 94.29%, specificity = 96.17%). The results confirm that feature subsets based on multiple bio-signals have the potential to identify patients with SA. The use of a smaller subset avoids dimensionality problems and reduces the computational load.

Recent studies in social robotics show that it can provide economic efficiency and growth in domains such as retail, entertainment, and active and assisted living (AAL). Recent work also highlights that users have the expectation of affordable social robotics platforms, providing focused and specific assistance in a robust manner. In this paper, we present the AMIRO social robotics framework, designed in a modular and robust way for assistive care scenarios. The framework includes robotic services for navigation, person detection and recognition, multi-lingual natural language interaction and dialogue management, as well as activity recognition and general behavior composition. We present AMIRO platform independent implementation based on a Robot Operating System (ROS). We focus on quantitative evaluations of each functionality module, providing discussions on their performance in different settings and the possible improvements. We showcase the deployment of the AMIRO framework on a popular social robotics platform&mdash, the Pepper robot&mdash, and present the experience of developing a complex user interaction scenario, employing all available functionality modules within AMIRO.

Inspection and repair interventions play vital roles in the asset management of railways. Autonomous mobile manipulators possess considerable potential to replace humans in many hazardous railway track maintenance tasks with high efficiency. This paper investigates the prospects of the use of mobile manipulators in track maintenance tasks. The current state of railway track inspection and repair technologies is initially reviewed, revealing that very few mobile manipulators are in the railways. Of note, the technologies are analytically scrutinized to ascertain advantages, unique capabilities, and potential use in the deployment of mobile manipulators for inspection and repair tasks across various industries. Most mobile manipulators in maintenance use ground robots, while other applications use aerial, underwater, or space robots. Power transmission lines, the nuclear industry, and space are the most extensive application areas. Clearly, the railways infrastructure managers can benefit from the adaptation of best practices from these diversified designs and their broad deployment, leading to enhanced human safety and optimized asset digitalization. A case study is presented to show the potential use of mobile manipulators in railway track maintenance tasks. Moreover, the benefits of the mobile manipulator are discussed based on previous research. Finally, challenges and requirements are reviewed to provide insights into future research.

Cyclodextrins, since their discovery in the late 19th century, were mainly regarded as excipients. Nevertheless, developments in cyclodextrin research have shown that some of these hosts can capture and include biomolecules, highlighting fatty acids and cholesterol, which implies that they are not inert and that their action may be used in specific medicinal purposes. The present review, centered on literature reports from the year 2000 until the present day, presents a comprehensive description of the known biological activities of cyclodextrins and their implications for medicinal applications. The paper is divided into two main sections, one devoted to the properties and applications of cyclodextrins as active pharmaceutical ingredients in a variety of pathologies, from infectious ailments to cardiovascular dysfunctions and metabolic diseases. The second section is dedicated to the use of cyclodextrins in a range of biomedical technologies.

Indonesia is currently undergoing the energy transition from heavily fossil fuel-dependent energy to cleaner sources of energy in order to achieve its net-zero emissions by 2060. In addition to reducing fossil fuel dependency, as one of the countries with the most geothermal reserves, the optimization of geothermal energy in Indonesia could be key to facilitating the energy transition. The objective of this paper is to elaborate on the transition process, which incorporates the destabilization of fossil fuel and the growth of geothermal energy, by analyzing the impact of both exogenous and endogenous factors on the supply chain structures of both sectors. This study employs workshop involving geothermal stakeholders in Indonesia, combined with the application of the Multi-Level Perspective (MLP) framework as the theoretical lens. The study found that energy demand, environmental awareness, energy regulations, energy supply chain, and geothermal potential breakthroughs are important aspects pertinent to the MLP components, namely the socio-technical landscape, socio-technical regime and niche innovations. The socio-technical landscapes are exogenous factors that pressurize the energy sector regime allowing the niche innovation, in the form of geothermal innovation, to penetrate the fossil fuel regime, allowing it to transition to a geothermal regime. The transition pathways include several measures that could break down the fossil fuel and build up geothermal energy, through a number of schemes and incentives.

Non-contact physiological measurements based on image sensors have developed rapidly in recent years. Among them, thermal cameras have the advantage of measuring temperature in the environment without light and have potential to develop physiological measurement applications. Various studies have used thermal camera to measure the physiological signals such as respiratory rate, heart rate, and body temperature. In this paper, we provided a general overview of the existing studies by examining the physiological signals of measurement, the used platforms, the thermal camera models and specifications, the use of camera fusion, the image and signal processing step (including the algorithms and tools used), and the performance evaluation. The advantages and challenges of thermal camera-based physiological measurement were also discussed. Several suggestions and prospects such as healthcare applications, machine learning, multi-parameter, and image fusion, have been proposed to improve the physiological measurement of thermal camera in the future.

In this paper, a new type of magnetic fluid deformable mirror (MFDM) with a two-layer layout of actuators is proposed to improve the correction performance for full-order aberrations with a high spatial resolution. The shape of the magnetic fluid surface is controlled by the combined magnetic field generated by the Maxwell coil and the two-layer array of miniature coils. The upper-layer actuators which have a small size and high density are used to compensate for small-amplitude high-order aberrations and the lower-layer actuators which have a big size and low density are used to correct large-amplitude low-order aberrations. The analytical model of this deformable mirror is established and the aberration correction performance is verified by the experimental results. As a new kind of wavefront corrector, the MFDM has major advantages such as large stroke, low cost, and easy scalability and fabrication.

Remarkable progress has been achieved in the detection of single stationary human. However, restricted by the mutual interference of multiple humans (e.g., strong sidelobes of the torsos and the shadow effect), detection and localization of the multiple stationary humans remains a huge challenge. In this paper, ultra-wideband (UWB) multiple-input and multiple-output (MIMO) radar is exploited to improve the detection performance of multiple stationary humans for its multiple sight angles and high-resolution two-dimensional imaging capacity. A signal model of the vital sign considering both bi-static angles and attitude angle of the human body is firstly developed, and then a novel detection method is proposed to detect and localize multiple stationary humans. In this method, preprocessing is firstly implemented to improve the signal-to-noise ratio (SNR) of the vital signs, and then a vital-sign-enhanced imaging algorithm is presented to suppress the environmental clutters and mutual affection of multiple humans. Finally, an automatic detection algorithm including constant false alarm rate (CFAR), morphological filtering and clustering is implemented to improve the detection performance of weak human targets affected by heavy clutters and shadow effect. The simulation and experimental results show that the proposed method can get a high-quality image of multiple humans and we can use it to discriminate and localize multiple adjacent human targets behind brick walls.

Simple Summary Ovarian cancer represents the most lethal gynecological malignancy. Since many new drugs have been recently introduced as adjunctive treatments for this pathology, an early prediction of outcome might be helpful to further improve outcomes. Radiomics represents a recent advancement, relying on extraction of quantitative features from imaging examinations. Indeed, clinical images, such as computed tomography images, may contain quantitative information, reflecting the underlying pathophysiology of a tumoral tissue. Radiomic analyses can be performed in tumor regions and metastatic lesions, as well as in normal tissues. The radiomic process relies on quantitative features, usually extracted by dedicated software, and then culminates in analysis and model building, according to a defined clinical question. This systematic review aims to evaluate association between radiomics based on computed tomography images and survival (in terms of overall survival and progression free survival) in ovarian cancer patients. Abstract The objective of this systematic review was to assess the results of radiomics for prediction of overall survival (OS) and progression free survival (PFS) in ovarian cancer (OC) patients. A secondary objective was to evaluate the findings of papers that based their analyses on inter-site heterogeneity. This systematic review was conducted according to the PRISMA statement. After the initial retrieval of 145 articles, the final systematic review comprised six articles. Association between radiomic features and OS was evaluated in 3/6 studies (50%); all articles showed a significant association between radiomic features and OS. Association with PFS was evaluated in 5/6 (83%) articles; the period of follow-up ranged between six and 36 months. All the articles showed significant association between radiomic models and PFS. Inter-site textural features were used for analysis in 2/6 (33%) articles. They demonstrated that high levels of inter-site textural heterogeneity were significantly associated with incomplete surgical resection in breast cancer gene-negative patients, and that lower heterogeneity was associated with complete resectability. There were some differences among papers in methodology; for example, only 3/6 (50%) articles included validation cohorts. In conclusion, radiomic models have demonstrated promising results as predictors of survival in OC patients, although larger studies are needed to allow clinical applicability.

The technique of acoustic emission (AE) source localization is critical for studying material failure mechanism and predicting the position of potential hazards. Most existing positioning methods heavily depend on the premeasured wave velocity and are not suitable for complex engineering practices where the wave velocity changes dynamically. To reduce the influence of measurement error of wave velocity on location accuracy, this paper proposes a new algebraic solution for AE source localization without premeasuring wave velocity. In this method, the nonlinear TDOA equations are established and linearized by introducing two intermediate variables. Then, by minimizing the sum of squared residuals of the linear TDOA equations with respect to the AE source coordinate and two intermediate variables separately, the optimal algebraic solution of the AE source coordinate in the least squares sense is obtained. A pencil-lead breaks experiment is performed to validate the positioning effectiveness of the proposed method. The results show that the new method improves the positioning accuracy by more than 40% compared with two pre-existing methods, and the minimum positioning accuracy of the proposed method can reach 1.12 mm. Moreover, simulation tests are conducted to further verify the location performance of the proposed method under different TDOA errors and the number of sensors.

The innovation of agricultural systems management is a determinant factor that guarantees adaptation to a new paradigm of global economy, environmental protection, and social requirements. The conventional concepts of innovation, applicable to new products and processes, do not consider many characteristics of the agricultural sector, such as social innovation and innovation resulting from new or renewed processes. Nevertheless, the overall impact of innovation on yields, competitiveness, and value can be hampered by the limited understanding or misinterpretation of Agriculture Innovation paradigms. For instance, the Rural Development Program (RDP) applies a restrict concept of innovation, being unable to embrace the full range of activities intended to implement new practices within the framework of the Agricultural Knowledge and Innovation System (AKIS). Stimulating innovation in agriculture demands a change in policy innovation of RDP in order to preserve natural resources and combine agricultural priorities and the rural environment with the concepts of innovation. This paper focuses on the different views of the concept of innovation within the Program of Operational Groups (OGs) of the European Innovation Partnership for Agricultural Productivity and Sustainability (EIP-AGRI), analyzing the Portuguese case study of the Lis Valley Irrigation District whose main innovation objective was to achieve and implement new processes of water management aiming at the conservation of natural resources as well as sustainable social and economic agricultural development. The Portuguese experience highlights why the application of innovation in agriculture may not reach the desirable outcomes info:eu-repo/semantics/publishedVersion

Funding: N.C. was funded by a doctoral grant (SFRH/BD/146881/2019) awarded by Fundação para a Ciência e Tecnologia (FCT). S.S. was supported by Agência Regional para o Desenvolvimento da Investigação, Tecnologia e Inovação (ARDITI) research fellowship in the scope of the H2020 project GoJelly. P.P. was funded by a PhD grant ref. M3.1.a/F/065/2015 by Fundo Regional de Ciência e Tecnologia (FRCT) and the program AÇORES 2020. A post-doctoral research fellowship by ARDITI (ARDITI–M1420-09-5369-FSE-000002) supported J.G.M. F.G. was endorsed by a post-doctoral research fellowship granted by ARDITI in the framework of project RAGES (ARDITI-RAGES-2019-001). R.F. was supported by the funding from project INTERWHALE (PTDC/CCI-COM/0450/2020) by FCT. Doctoral fellowships were financially supported S.C. by ARDITI (ARDITI-M1420-09-5369-FSE-000002). R.S. was supported by a research fellowship in the framework of project PLASMAR+(MAC2/1.1a/347). J.C.-C. is funded by national funds through FCT under the Scientific Employment Stimulus—Institutional Call—[CEECINST/00098/2018]. This work was partially funded by MIMAR+(MAC2/4.6.d/249) in the INTERREG MAC 2014–2020 Programme framework. This study also had the support of Fundação para a Ciência e Tecnologia (FCT), Portugal, through the strategic project (UIDB/04292/2020) granted to MARE UI&IUIDB/04292/2020. Finally, the present paper benefited from underwater surveys during the expedition ‘MARE@Porto Santo 20200 conducted by MARE-Madeira. Current trends in the global climate facilitate the displacement of numerous marine species from their native distribution ranges to higher latitudes when facing warming conditions. In this work, we analyzed occurrences of a circumtropical reef fish, the spotfin burrfish, Chilomycterus reticulatus (Linnaeus, 1958), in the Madeira Archipelago (NE Atlantic) between 1898 and 2021. In addition to available data sources, we performed an online survey to assess the distribution and presence of this species in the Madeira Archipelago, along with other relevant information, such as size class and year of the first sighting. In total, 28 valid participants responded to the online survey, georeferencing 119 C. reticulatus sightings and confirming its presence in all archipelago islands. The invasiveness of the species was screened using the Aquatic Species Invasiveness Screening Kit. Five assessments rated the fish as being of medium risk of establishing a local population and becoming invasive. Current temperature trends might have facilitated multiple sightings of this thermophilic species in the Madeira Archipelago. The present study indicates an increase in C. reticulatus sightings in the region. This underlines the need for updated comprehensive information on species diversity and distribution to support informed management and decisions. The spread of yet another thermophilic species in Madeiran waters provides further evidence of an ongoing tropicalization, emphasizing the need for monitoring programs and the potential of citizen science in complementing such programs. info:eu-repo/semantics/publishedVersion

In this paper we examine the polymer density distribution of gel particles and its effect on solvent diffusivity through the polymer network. In order to access the inner particle regions, external polymer layers were removed by plasma etching, thus reducing them from the outside. Higher polymer densities after erosion showed internal heterogeneity, with the density increasing towards the center of the particles. An exponential decay polymer density model is proposed, and the spatial relaxation length measured. The diffusion of solvent through the particles, before and after the plasma oxidation, revealed a correlation between the diffusion coefficient and the internal density.

Californians Linking Action with Science for Prevention of Breast Cancer (CLASP-BC) is part of California Breast Cancer Research Program’s (CBCRP) Initiative strategic priority to disseminate and implement high-impact, population-based primary prevention interventions. CLASP-BC is informed by six years of funded program dissemination and implementation (D&I) research and evaluation conducted by the Canadian Partnership Against Cancer (CPAC) through its Coalitions Linking Action and Science for Prevention (CLASP). In its second phase, CLASP-BC will fund multi-sector, multi-jurisdictional initiatives that integrate the lessons learned from science with the lessons learned from practice and policy to reduce the risk of developing breast cancer and develop viable and sustainable infrastructure models for primary prevention breast cancer programs and research evidence implementation. Applications will be solicited from research, practice, policy, and community teams to address one or more of the intervention goals for the 23 risk factors identified in Paths to Prevention: The California Breast Cancer Primary Prevention Plan (P2P), expanding upon existing primary prevention efforts into two or more California jurisdictions, focused on disadvantaged, high risk communities with unmet social needs. The lessons learned from CLASP-BC will be widely disseminated within the participating jurisdictions, across California and, where applicable, to jurisdictions outside the state.

A key issue in the field of kidney transplants is the analysis of transplant recipients’ survival. By means of the information obtained from transplant patients, it is possible to analyse in which cases a transplant has a higher likelihood of success and the factors on which it will depend. In general, these analyses have been conducted by applying traditional statistical techniques, as the amount and variety of data available about kidney transplant processes were limited. However, two main changes have taken place in this field in the last decade. Firstly, the digitalisation of medical information through the use of electronic health records (EHRs), which store patients’ medical histories electronically. This facilitates automatic information processing through specialised software. Secondly, medical Big Data has provided access to vast amounts of data on medical processes. The information currently available on kidney transplants is huge and varied by comparison to that initially available for this kind of study. This new context has led to the use of other non-traditional techniques more suitable to conduct survival analyses in these new conditions. Specifically, this paper provides a review of the main machine learning methods and tools that are being used to conduct kidney transplant patient and graft survival analyses.

With the growth of the internet of things (IoT), many challenges like information security and privacy, interoperability/standard, and regulatory and legal issues are arising. This work focused on the information security issue, which is one of the primary challenges faced by connected systems that needs to be resolved without impairing system behaviour. Information, which is made available on the Internet by the things, varies from insensitive information (e.g., readings from outdoor temperature sensors) to extremely sensitive information (e.g., video stream from a camera) and needs to be secured over the Internet. Things which utilise cameras as a source of information pertain to a subclass of the IoT called IoVT (internet of video things). This paper presents secured and unsecured video latency measurement results over the Internet for a marine ROV (remotely operated vehicle). A LabVIEW field programmable gate arrays (FPGAs)-based bump-in-the-wire (BITW) secure core is used to provide an AES (advanced encryption standard)-enabled security feature on the video stream of an IoVT node (ROV equipped with a live-feed camera). The designed LabVIEW-based software architecture provides an option to enable/disable the AES encryption for the video transmission. The latency effects of embedding encryption on the stream with real-time constraints are measured and presented. It is found that the encryption mechanism used does not greatly influence the video feedback performance of the observed IoVT node, which is critical for real-time secure video communication for ROV remote control and piloting. The video latency measurement results are taken using 128, 256 and 512 bytes block lengths of AES for both H.264 and MJPEG encoding schemes transmitted over both TCP and UDP transmission protocols. The latency measurement is performed in two scenarios (i.e., with matching equipment and different equipment on either end of the transmission).

The inorganic and organic property values of general orgainc groups are re-proposed here. The inorganic (I) and organic (O) property values of drug and biological molecules or groups can be calculated based on their group values. The calculation can be easily done on line through Javascript. Similar calculation can be done for the drug and biological molecular group electronegativity according to the author's published paper. The calculation of lipophilicity (pi or logP) parameter of (macro)molecules (like proteins) can also be done on-line through Javascript. Two equations expressed with I and O are provided here to define the hydrophobicity of each amino acid. The correlations of inorganic and organic property values with other parameters are also discussed. These calculated papameters combined with other papameters can be used for QSAR studies in some drug molecules. Some applications are also disscussed in this paper.

Chimeric Antigen Receptor (CAR) T-cell therapy has demonstrated high rates of response in recurrent B-cell Acute Lymphoblastic Leukemia in children and young adults. Despite this success, a fraction of patients' experience relapse after treatment. Relapse is often preceded by recovery of healthy B cells, which suggests loss or dysfunction of CAR T-cells in bone marrow. This site is harder to access, and thus is not monitored as frequently as peripheral blood. Understanding the interplay between B cells, leukemic cells, and CAR T-cells in bone marrow is paramount in ascertaining the causes of lack of response. In this paper, we put forward a mathematical model representing the interaction between constantly renewing B cells, CAR T-cells, and leukemic cells in the bone marrow. Our model accounts for the maturation dynamics of B cells and incorporates effector and memory CAR T-cells. The model provides a plausible description of the dynamics of the various cellular compartments in bone marrow after CAR T infusion. After exploration of the parameter space, we found that the dynamics of CAR T product and disease were independent of the dose injected, initial B-cell load, and leukemia burden. We also show theoretically the importance of CAR T product attributes in determining therapy outcome, and have studied a variety of possible response scenarios, including second dosage schemes. We conclude by setting out ideas for the refinement of the model., This work was partially supported by the Fundacion Espanola para la Ciencia y la Tecnologia (UCA PR214), the Asociacion Pablo Ugarte (APU, Spain), Junta de Comunidades de Castilla-La Mancha (SBPLY/17/180501/000154), Ministry of Science and Technology, Spain (PID2019110895RB-I00), and Inversion Territorial Integrada de la Provincia de Cadiz (ITI-0038-2019).

The aim of this paper is to evaluate the effective properties of composite materials with periodic random packing of ellipsoids of different volume fractions and aspect ratios. Therefore, we employ computational homogenization. A very efficient MD-based method is applied to generate the periodic random packing of the ellipsoids. The method is applicable even for extremely high volume fractions up to 60%. The influences of the volume fraction and aspect ratio on the effective properties of the composite materials are studied in several numerical examples. NSFC/51474157 National Basic Research Program of China/973 Shanghai Qimingxing Program/16QA1404000 State Key Laboratory for Geomechanics and Deep Underground Engineering, China University of Mining & Technology Key/SKLGDUEK1526