Miracle-dz/UniFAR-FTUs huggingface dataset:
Development and characterisation of silsesquioxane-polycaprolactone nanocomposite scaffolds for use in small intestinal tissue engineering

Tissue engineering of small intestine aims to provide a cure to patients suffering from short bowel syndrome by increasing the absorptive surface through neo-intestinal mucosal tissue. So far, preliminary in vivo attempts by a research team in the USA have shown regeneration of neo-intestinal mucosa in rat models with some success; however experiments in this complex field of tissue engineering still remain in infancy and far from clinical use. A fresh perspective is required to further investigate all the three aspects of tissue engineering, namely, the polymer scaffold, the cell supply, and the biomolecules. The concept of nanocomposite polymer is rapidly emerging and has generated a lot of enthusiasm in tissue engineering due to their high surface to volume ratio and hence enhanced performance. This work was focussed to develop and characterise scaffolds for small intestinal tissue engineering using a new nanocomposite polymer of polycaprolactone and silsesquixane, developed in our laboratory. An in vitro study was also performed to test the scaffolds for cell viability and proliferation using rat’s intestinal epithelial cells. Our results have shown that biodegradable polycaprolactone-silsesquioxane nanocomposite can be fabricated in desired scaffold morphology using simple techniques like particulate leaching, and that it supports intestinal cell growth and proliferation. Future studies incorporating these scaffolds for in vivo use in animal models need to be carried out in order to investigate further about their ability to withstand natural forces within the abdomen, and whether they support cell growth based on principles of cell migration, before a more definitive and continuous cell supply is available in form of stem cells cued specifically to intestinal lineage.
Air quality monitoring system for indoor environments using IoT

In this work, we have used an IoT based approach along with required mathematical formulae to ascertain the quality of air in different indoor environments. By using the concept of an embedded technology, various sensors are connected to collect the data in different environments. The cloud technology is used for storing the sensed data. This collected data is stored in the information cloud and then inquired for the analysis of any environmental condition. This model is used to record and analyze such data in ThingSpeak. ThingSpeak is an analytic data platform for which IoT can be used as aggregation, visualization and analysis of live data steam in cloud. Moreover, Python codes are written for different mathematical formulae which are used in the ThingSpeak to check the environment condition. It has been observed that the graphical representation of environmental parameters in ThingSpeak gives the basic idea about the environment condition of that particular region.In this work, we have used an IoT based approach along with required mathematical formulae to ascertain the quality of air in different indoor environments. By using the concept of an embedded technology, various sensors are connected to collect the data in different environments. The cloud technology is used for storing the sensed data. This collected data is stored in the information cloud and then inquired for the analysis of any environmental condition. This model is used to record and analyze such data in ThingSpeak. ThingSpeak is an analytic data platform for which IoT can be used as aggregation, visualization and analysis of live data steam in cloud. Moreover, Python codes are written for different mathematical formulae which are used in the ThingSpeak to check the environment condition. It has been observed that the graphical representation of environmental parameters in ThingSpeak gives the basic idea about the environment condition of that particular region.
Density‐Driven Convection in a Fractured Porous Media: Implications for Geological CO2 Storage

Dissolution trapping is one of the primary mechanisms of carbon dioxide (CO2) storage in a geological formation. In this study, a numerical model was used to examine the impacts of single and multiple fractures on the transport of dissolved CO2 plumes in various geological settings. The effects of the fracture angle, fracture‐matrix permeability ratio, fracture intersection, and matrix heterogeneity on density‐driven CO2 convection were systematically investigated. The fractures were found to play time‐varying roles in both homogeneous and heterogeneous media by serving as preferential pathways for both CO2‐rich plumes (fingers) and CO2‐free water. The competition between the enhancement of convective mixing and the inhibition of finger growth by the upward flow of freshwater generated a complex flow system. The interaction between the strong upward flow of freshwater through the fractures and the falling CO2‐rich fingers through the porous matrix induced a positive feedback, resulting in accelerated domain‐scale circulation and CO2 dissolution. While the CO2‐rich fingers grew relatively evenly at the top boundary in the homogeneous media, they selectively developed through the high permeable zones in the heterogeneous media. Compared with homogeneous media, the heterogeneous media preserving fractures particularly generated a more dynamic fracture‐matrix mass transfer, resulting in more rapid CO2 dissolution. The findings of this study were extended to examine the effects of fracture connectivity on the enhancement of CO2 transport and dissolution on a field scale.
Aspects of human physical and behavioural evolution during the last 1 million years

This paper reviews some of the main advances in our understanding of human evolution over the last 1 million years, presenting a holistic overview of a field defined by interdisciplinary approaches to studying the origins of our species. We begin by briefly summarizing the climatic context across the Old World for the last 1 million years before directly addressing the fossil and archaeological records. The main themes in this work explore (i) recent discoveries in the fossil record over the last 15 years, such as Homo naledi and Homo floresiensis; (ii) the implications of palaeogenetics for understanding the evolutionary history of, and relationships between, Neanderthals, Denisovans and Homo sapiens; (iii) the interplay between physiology and metabolic demand, landscape use, and behavioural adaptations in the evolution of morphological and behavioural innovation; and (iv) recent advances in archaeological understanding for the behavioural record, in particular that of the Neanderthals. This paper seeks to provide a broad‐scale, holistic perspective of our current understanding of human evolution for the last 1 Ma, providing a reference point for researchers that can be built upon as new discoveries continue to develop the landscapes of human evolution. © 2019 The Authors. Journal of Quaternary Science Published by Wiley Periodicals, Inc.
Philosophers Explore The Matrix

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Distributed Stability Analysis for Power Systems Under Persistent Disturbance

The continued growth of renewable energy penetration in power systems calls for an efficient and scalable approach for stability analysis. This paper proposes a new stability index called $\mathcal{L}_{2}$ stability index (LSI) for power systems under persistent disturbance by combining the concepts of $\mathcal{L}_{2}$ gain and output-differential passivity (OD-passivity). The proposed stability index provides a quantitative way to measure the power system stability under external disturbances such as power fluctuations due to renewable generation. We also put forward a distributed approach to computing LSI and implement it in three typical power devices, i.e., synchronous generators (SGs), conventional droop-controlled inverters, and quadratic droop-controlled inverters. Case studies on two IEEE 39-bus systems verify the theoretical analysis in this paper.
Connectivity planning for closed-chain reconfiguration

Modular reconfigurable robots can change their connectivity from one arrangement to another. Performing this change involves a difficult planning problem. We study this problem by representing robot configurations as graphs, and giving an algorithm that can transform any configuration of a robot into any other in O (log n) steps. Here n is the number of modules which can attach to more than two other modules. We also show that O(log n) is best possible.
Vulnerability of volcanic loose soils having cementation and crushable particles

In Japan, a multitude of slope disasters occur annually, resulting in often severe loss of human life. On occasion, disasters that occur at very gentle slopes and disasters that flow long distance, associated with destructive energy, are observed. In such cases, the trigger layer often consists of volcanic soils with extremely high void ratios and external triggers, including earthquake or heavy rainfall, increase the risk of slope disasters. These volcanic soils are often characterised by an extremely loose structure and are either retained mainly by weak cementation or are composed of crushable particles having intra voids. Although the cause of destructive long-distance flow has been explained by liquefaction, there are some observed disasters in which the trigger layer was not fully saturated, i.e. liquefaction should not be considered as a major cause. Focusing on the fact that long-distance flow or gentle slope flow, disasters are triggered by volcanic soil layers of extremely loose structure, artificial loose soil samples were prepared in the laboratory. These samples were prepared with cementation between particles and with crushable particles. In this study, deformation and strength characteristics of the extremely loose soils were investigated by conducting CD triaxial tests. It is revealed that such extremely loose soils can be vulnerable after the weakly cemented structure collapses as a result of external factors such as earthquakes.
Creating a value proposition with a social media strategy for talent acquisition

Abstract The talent acquisition process involves complex interactions between potential job seekers and the enterprises that seek to ultimately employ them. Although both parties are aligned to produce an optimal outcome, the emergence of social media technologies and a workforce adept at using them offers new challenges for companies. At the same time, studies of millennials (i.e. people born from the early 1980s to 2000) reveal that they are a large demographic currently seeking employment and that one of their characteristics is a values-orientation (i.e. wanting their jobs and companies to make a difference in the world). Just as talent managers are recognising the changing attitudes of their potential workforce, companies are becoming aware that they need to seek talent proactively rather than relying on traditional job postings. Social media strategies provide opportunities for companies to reach out to today’s job seekers by using new types of engagement through direct contact and personalization. This paper investigates opportunities and challenges in utilising social media during the recruitment process based on the Elaboration Likelihood Model and the understand-deliver-measure cycle. We present two case studies with a large and mid-sized firm to illustrate how companies can utilise social media to create a value proposition for job seekers and personalise content to enhance talent acquisition.
Resin Flow in Loblolly and Shortleaf Pines Used by Red-Cockaded Woodpeckers

We measured resin flow in loblolly (Pinus taeda L.) and shortleaf (Pinus echinata Mill.) pines in stands used by red-cockaded woodpecker, Picoides borealis (Vieillot), in the Angelina and Davy Crockett National Forests in eastern Texas. We also measured resin flow in a mature loblolly pine stand not used by the woodpeckers. Resin flow varied by study area, species, and stand position. In woodpecker stands, pines experiencing low levels of competition seemed better able to tolerate the continual resin drainage associated with red-cockaded woodpecker resin well pecking. In the Angelina National Forest, all new cavity trees excavated during the study were on forest edges. In the non-woodpecker stand, edge trees had significantly better resin flow. These results indicate that the woodpeckers choose trees most likely to be good resin producers. They also indicate that silviculture in loblolly and shortleaf pine stands should favor edge and an open stand habit when red-cockaded woodpeckers are a major management consideration and that potential resin production can be measured in both cavity pines, and pines being considered for red-cockaded woodpecker introduction.
Modelling fault reactivation with characteristic stress-drop terms

Abstract. Predicting shear failure that leads to the reactivation of faults during the injection of fluids in the subsurface is difficult since it inherently involves an enormous complexity of flow processes interacting with geomechanics. However, understanding and predicting induced seismicity is of great importance. Various approaches to modelling shear failure have been suggested recently. They are all dependent on the prediction of the pressure and stress field, which requires the solution of partial differential equations for flow and for geomechanics. Given a pressure and corresponding mechanical responses, shear slip can be detected using a failure criterion. We propose using characteristic values for stress drops occurring in a failure event as sinks in the geomechanical equation. This approach is discussed in this article and illustrated with an example.
Direct O2 control on the partitioning between denitrification and dissimilatory nitrate reduction to ammonium in lake sediments

Abstract. Lacustrine sediments are important sites of fixed-nitrogen (N) elimination through the reduction of nitrate to N2 by denitrifying bacteria, and they are thus critical for the mitigation of anthropogenic loading of fixed N in lakes. In contrast, dissimilatory nitrate reduction to ammonium (DNRA) retains bioavailable N within the system, promoting internal eutrophication. Both processes are thought to occur under oxygen-depleted conditions, but the exact O2 concentration thresholds particularly of DNRA inhibition are uncertain. In O2 manipulation laboratory experiments with dilute sediment slurries and 15NO3- additions at low- to sub-micromolar O2 levels, we investigated how, and to what extent, oxygen controls the balance between DNRA and denitrification in lake sediments. In all O2-amended treatments, oxygen significantly inhibited both denitrification and DNRA compared to anoxic controls, but even at relatively high O2 concentrations (≥70 µmol L−1), nitrate reduction by both denitrification and DNRA was observed, suggesting a relatively high O2 tolerance. Nevertheless, differential O2 control and inhibition effects were observed for denitrification versus DNRA in the sediment slurries. Below 1 µmol L−1 O2, denitrification was favoured over DNRA, while DNRA was systematically more important than denitrification at higher O2 levels. Our results thus demonstrate that O2 is an important regulator of the partitioning between N loss and N recycling in sediments. In natural environments, where O2 concentrations change in near-bottom waters on an annual scale (e.g., overturning lakes with seasonal anoxia), a marked seasonality with regards to internal N eutrophication versus efficient benthic fixed-N elimination can be expected.
Stabilization and recycling of contaminated marine sediments

The paper deals with the treatment and reuse of submarine sediments, i.e. a relevant environmental issue due to the annual huge quantities of dredged sediments (over half contaminated) in Europe. In a vision of sustainability and circular economy, stabilization and solidification (S/S) treatments represent an interesting solution for both environmental protection and reuse of sediments in engineering works. The investigation involved polluted clayey sediments taken up to depths of about 1.5m from the seafloor of the Gulf of Taranto (South of Italy). The research investigates the effects of a treatment with cement and lime enhanced by the addition of green additives, such as active carbon and biochar, for chemical remediation. The last one is a promising and cheap adsorbent material, that is the by-product of - mainly - agricultural waste pyrolysis. The first results suggest that appropriate mix designs and curing times could allow the reuse of sediments by both improving their geotechnical characteristics and making them environmentally acceptable in accordance to end-of-waste criteria.
Model-Based Dereverberation for Speech Recognition

This paper presents an effective method for suppressing reverberation and noise for speech signals. Based on a sim­ ple model which considers basic principles of room acous­ tics the power spectral density of the reverberation is es­ timated. Spectral subtraction is then used to weight the spectrum of the input signal dynamically. The method is characterized by its robustness and efficiency. It enhances speech recognition performance considerably for single­ channel as well as for multi-channel systems.
AUV Bathymetric Simultaneous Localisation and Mapping Using Graph Method

Although topographic mapping missions and geological surveys carried out by Autonomous Underwater Vehicles (AUVs) are becoming increasingly prevalent, the lack of precise navigation in these scenarios still limits their application. This paper deals with the problems of long-term underwater navigation for AUVs and provides new mapping techniques by developing a Bathymetric Simultaneous Localisation And Mapping (BSLAM) method based on graph SLAM technology. To considerably reduce the calculation cost, the trajectory of the AUV is divided into various submaps based on Differences of Normals (DoN). Loop closures between submaps are obtained by terrain matching; meanwhile, maximum likelihood terrain estimation is also introduced to build weak data association within the submap. Assisted by one weight voting method for loop closures, the global and local trajectory corrections work together to provide an accurate navigation solution for AUVs with weak data association and inaccurate loop closures. The viability, accuracy and real-time performance of the proposed algorithm are verified with data collected onboard, including an 8 km planned track recorded at a speed of 4 knots in Qingdao, China.
West Greenland ice sheet retreat history reveals elevated
precipitation during the Holocene thermal maximum

Abstract. We investigate changing precipitation patterns in the Kangerlussuaq region of west central Greenland during the Holocene thermal maximum, using a new chronology of ice sheet terminus position through the Holocene and a novel inverse modeling approach based on the unscented transform (UT). The UT is applied to estimate changes in annual precipitation in order to reduce the misfit between modeled and observed terminus positions. We demonstrate the effectiveness of the UT for time-dependent data assimilation, highlighting its low computational cost and trivial parallel implementation. Our results indicate that Holocene warming coincided with elevated precipitation, without which modeled retreat in the Kangerlussuaq region is more rapid than suggested by observations. Less conclusive is if high temperatures during the HTM were specifically associated with a transient increase in precipitation, as the results depend on the assumed temperature history. The importance of precipitation in controlling ice sheet extent during the Holocene underscores the importance of Arctic sea ice loss and changing precipitation patterns on the future stability of the GrIS.
Flood risk in a range of spatial perspectives – from global to local scales

Abstract. The present paper examines flood risk (composed of hazard, exposure, and vulnerability) in a range of spatial perspectives – from the global to the local scale. It deals with observed records, noting that flood damage has been increasing. It also tackles projections for the future, related to flood hazard and flood losses. There are multiple factors driving flood hazard and flood risk and there is a considerable uncertainty in our assessments, and particularly in projections for the future. Further, this paper analyses options for flood risk reduction in several spatial dimensions, from global framework to regional to local scales. It is necessary to continue examination of the updated records of flood-related indices, trying to search for changes that influence flood hazard and flood risk in river basins.
Conceptualizing Online Discussion Value: A Multidimensional Framework for Analyzing User Comments on Mass-Media Websites

This chapter provides a micro-framework for analyzing the quantity and quality of online user comments on mass-media websites. On one dimension, news factors of news items and discussion factors of existing user comments are assumed to indicate the relevance of participating in online discussions. On a second dimension, specific motivational, social, and design factors are influential when reconstructing users’ decisions to participate in online discussions and when analyzing the content of online user comments. The two dimensions in combination describe the discussion value of news items. Potential applications of this framework on other forms of interpersonal communication are discussed.
Soil Texture Estimation Using Radar and Optical Data from Sentinel-1 and Sentinel-2

This paper discusses the combined use of remotely sensed optical and radar data for the estimation and mapping of soil texture. The study is based on Sentinel-1 (S-1) and Sentinel-2 (S-2) data acquired between July and early December 2017, on a semi-arid area about 3000 km2 in central Tunisia. In addition to satellite acquisitions, texture measurement samples were taken in several agricultural fields, characterized by a large range of clay contents (between 13% and 60%). For the period between July and August, various optical indicators of clay content Short-Wave Infrared (SWIR) bands and soil indices) were tested over bare soils. Satellite moisture products, derived from combined S-1 and S-2 data, were also tested as an indicator of soil texture. Algorithms based on the support vector machine (SVM) and random forest (RF) methods are proposed for the classification and mapping of clay content and a three-fold cross-validation is used to evaluate both approaches. The classifications with the best performance are achieved using the soil moisture indicator derived from combined S-1 and S-2 data, with overall accuracy (OA) of 63% and 65% for the SVM and RF classifications, respectively.