Miracle-dz/UniFAR-FTUs huggingface dataset:
An Intelligent Coaching Prototype for Elderly Care

The world ageing problem is prompting new sustainable ways to support elderly people. As such, it is important to promote personalized and intelligent ways to assure the active and healthy ageing of the population. Technological breakthroughs have led to the development of personalized healthcare systems, capable of monitoring and providing feedback on different aspects that can improve the health of the elderly person. Furthermore, defining motivational strategies to persuade the elderly person to be healthier and stay connected to such systems is also fundamental. In this work, a coaching system is presented, especially designed to support elderly people and motivate them to pursue healthier ways of living. To do this, a coaching application is developed using both a cognitive virtual assistant to directly interact with the elderly person and provide feedback on his/her current health condition, and several gamification techniques to motivate the elderly person to stay engaged with the application. Additionally, a set of simulations were performed to validate the proposed system in terms of the support and feedback provided to the user according to his progress, and through interactions with the cognitive assistant.
Stepwise evolution of the Asian summer monsoon during the Holocene revealed by a stalagmite record from Heifeng Cave, Southwest China

The abrupt changes of the Asian summer monsoon (ASM) during the Holocene have long been of interest to environmental scientists. Here, RAMPFIT and Bayesian Change Point (BCP) analyses are applied to analyze the stalagmite δ18O record from Heifeng Cave in southern China, and the results show that it is characterized by a distinct stepwise pattern of variation which can be divided into six stages (Stages, S) and five transitional phases (Transitions, T). In the early Holocene, when Northern Hemisphere summer insolation (NHSI) was at its maximum, the ASM underwent step-like increases in strength, comprising two stages. With the decrease in NHSI during the middle to late-Holocene, the weakening of ASM intensity was characterized by further step-like changes comprising three stages. The transitional phases of the monsoon are broadly correlative with millennial-scale monsoon weakening events associated with Bond events in the North Atlantic region, suggesting that the stepwise evolution of the ASM during the Holocene was caused by the combined effects of changes in NHSI and Bond events. We propose that Bond events may have acted as triggers that caused the ASM to cross a critical threshold, prompting a shift from one regime to another.
Design Strategy for Nanostructured Arrays of Metallodielectric Cuboids to Systematically Tune the Optical Response and Eliminate Spurious Bulk Effects in Plasmonic Biosensors

Plasmonic biosensors are a powerful tool for studying molecule adsorption label-free and with high sensitivity. Here, we present a systematic study on the optical properties of strictly regular nanostructures composed of metallodielectric cuboids with the aim to deliberately tune their optical response and improve their biosensing performance. In addition, the patterns were tested for their potential to eliminate spurious effects from sensor response, caused by refractive index changes in the bulk solution. Shifts in the plasmonic spectrum are exclusively caused by the adsorbing molecules. For this purpose, nanopatterns of interconnected and separated cubes with dimensions ranging from 150 to 600 nm have been fabricated from poly(methyl methacrylate) using electron-beam lithography followed by metallization with gold. It is shown that a small lateral pattern size, a high aspect ratio, and short connection lengths are favorable to generate extinction spectra with well-separated and pronounced peaks. Furthermore, for selected nanostructures, we have been able to identify reflection angles for which the influence of the bulk refractive index on the position of the plasmonic peaks is negligible. It is shown that sensor operation under these angles enables monitoring of in situ biomolecule adsorption with high sensitivity providing a promising tool for high-throughput applications.
Robotic Rotational Positioning of End-Effectors for Micromanipulation

Precise rotational positioning of end-effectors under microscopy is crucial for robotic micromanipulation. However, the end-effector is presently limited to a fixed orientation, which is manually set before a given micromanipulation task, lacking accuracy and versatility of in situ reorientation. In this article, we present a unified framework for rotationally positioning the end-effector in three dimensions by establishing a general rotational model, developing a detection method within the limited field of view under microscopy, and designing a three-loop control strategy that adapts to different experimental requirements and model parameters. In experiments, a standard angled micropipette was used as the end-effector to verify the validity of the proposed methods. The performance was evaluated experimentally where the micropipette was robotically rotated to an arbitrarily desired orientation with an average orientation error less than $2^\circ$. In the experiments of sperm manipulation, the in situ micropipette orientation control capability improved the success rate of sperm immobilization and achieved dexterous robotic sperm orientation for facile aspiration.
An attention-based deep learning model for citywide traffic flow forecasting

ABSTRACT Prompt and accurate traffic flow forecasting is a key foundation of urban traffic management. However, the flows in different areas and feature channels (inflow/outflow) may correspond to different degrees of importance in forecasting flows. Many forecasting models inadequately consider this heterogeneity, resulting in decreased predictive accuracy. To overcome this problem, an attention-based hybrid spatiotemporal residual model assisted by spatial and channel information is proposed in this study. By assigning different weights (attention levels) to different regions, the spatial attention module selects relatively important locations from all inputs in the modeling process. Similarly, the channel attention module selects relatively important channels from the multichannel feature map in the modeling process by assigning different weights. The proposed model provides effective selection and attention results for key areas and channels, respectively, during the forecasting process, thereby decreasing the computational overhead and increasing the accuracy. In the case involving Beijing, the proposed model exhibits a 3.7% lower prediction error, and its runtime is 60.9% less the model without attention, indicating that the spatial and channel attention modules are instrumental in increasing the forecasting efficiency. Moreover, in the case involving Shanghai, the proposed model outperforms other models in terms of generalizability and practicality.
An Analysis of SE and MBSE Concepts to Support Defence Capability Acquisition

Abstract : System modelling has been an enduring method of enquiry supporting systems analysis and design synthesis in systems engineering for decades. New generation systems modelling tools provide sophisticated modelling capability, coined Model-based Systems Engineering (MBSE). The underpinning fundamentals of systems engineering and MBSE are scrutinised in the context of the current Defence capability development process and enterprise architecture initiatives. The capabilities, relevance, and utility of new generation MBSE tools and methodologies are then examined, contrasting Defence and industry perspectives to reveal potential implications for Defence. Potential benefits to Defence are highlighted together with potential issues of concern. Related aspects of software engineering, enterprise engineering, enterprise architecting and operations research are also clarified to assist unravelling some of the complexities and interdependencies between the respective professional disciplines.
A Machine Learning Pipeline for Document Extraction

F I R S T B R E A K I V O L U M E 4 0 I F E B R U A R Y 2 0 2 2 7 3 can be applied, and the figures need to be located before they can be classified. The automated pipeline is run on a user-specified dataset, which can consist of various file types, such as PDF, Word doc, Excel and CSV, and different image files, such as TIFF and PNG, etc. After initial ingestion, each of the components will be triggered in turn automatically as soon as its dependencies have completed successfully. There are two advantages to our automated approach. Metadata in the file path or manual labelling can only support a single high-level label. Using the pipeline, a much more granular classification of the contents can be achieved at a paragraph or page object level. Secondly, many documents can be processed much more quickly. As an illustration, a previous project took 16 people 14 months to complete, whereas a recent equivalent project using the pipeline took 2 people 1 month, including computing time. This is a hundred times faster! This article will focus on the machine learning steps in our pipeline, namely document layout analysis, image classification, named entity recognition and table cell classification. In recent times, machine learning has become increasingly dominated by deep learning models. These are data-hungry algorithms that need to be trained on large volumes of labelled input data. For A machine learning pipeline for document extraction
Fixing the identity of Scolelepis squamata (Annelida: Spionidae) – neotype designation, redescription and DNA barcode sequences

The identity of Scolelepis squamata (O.F. Müller, 1806) (Spionidae) has long been under debate. For clarification of this problem a collection of Scolelepis specimens at the type locality of this species, the island of Helgoland (North Sea) and in particular the Helgoland Dunes, has been undertaken. Based on morphological and molecular studies the occurrence of only one Scolelepis species can be reported in the eulittoral zone. The specimens are in good accordance with the morphology of S. squamata. Based on these newly collected specimens S. squamata is redescribed and illustrated comprehensively, and, in addition, molecular information on several markers is provided. A neotype has been designated and deposited in the collection of the Zoological Museum at Hamburg University, Germany. Molecular phylogenetic analyses based on COI, 18S rRNA and 28S rRNA reveal little genetic diversity along the Atlantic coast from Helgoland to Portugal and thus support the occurrence of S. squamata in these coastal regions of the Eastern North Atlantic Ocean. Our results further indicate the presence of a distinct Scolelepis species in the Black Sea, which is closely related to S. squamata. Also, S. mesnili is reinstated as a valid species. Furthermore, it is shown that several earlier genetic studies had misidentified S. squamata specimens wrongly as S. foliosa or S. bonnieri, highlighting the need for the taxonomic redescription as well as for providing DNA barcodes from unambiguously identified specimens. http://zoobank.org/urn:lsid:zoobank.org:pub:0D6C3783-FF06-4D84-8D92-B8691E88F0B9
Understanding social impact assessment through public value theory

Our research focuses on understanding the use that work integration social enterprises (WISEs) make of performance measurement models such as social impact assessment in their relations with public stakeholders. We carry out a comparative study between France and Denmark which are the two OECD members showing the highest level of social spending. Using public value theory as the pivot point of our analytical framework, we identify seven strategic intents that contribute to explain the use of performance measurement by WISEs. The use of Public Value theory shines a light on the unique set of problems that WISEs face when dealing with their public stakeholder, which is absent from the performance models that are promoted by current policy initiatives or by impact investors.
The complete chloroplast genome of the aromatic tree species Cinnamomum tenuipile Kosterm (Lauraceae)

Abstract Cinnamomum tenuipile Kosterm is a precious aromatic tree in Lauraceae. To better determine its phylogenetic location with other Cinnamomum species, the chloroplast genome of C. tenuipile was sequenced. The complete chloroplast genome size is 152,761 bp, consisting of a pair of inverted repeats (IRa/b) with a length of 20,074 bp separated by a large single-copy region (LSC) and a small single-copy region (SSC) which are 93,685 and 18,928 bp, respectively. The overall GC content of the cp genome is 39.16%. The maximum-likelihood phylogenetic tree showed that C. tenuipile is more closely related to C. aromaticum, providing new insight into the evolution of Lauraceae.
Intuition as Emergence: Bridging Psychology, Philosophy and Organizational Science

Accelerating environmental uncertainty and the need to cope with increasingly complex market and social demands, combine to create high value for the intuitive approach to decision-making at the strategic level. Research on intuition suffers from marked fragmentation, due to the existence of disciplinary silos based on diverse, apparently irreconcilable, ontological and epistemological assumptions. Not surprisingly, there is no integrated interdisciplinary framework suitable for a rich account of intuition, contemplating how affect and cognition intertwine in the intuitive process, and how intuition scales up from the individual to collective decision-making. This study contributes to the construction of a broad conceptual framework, suitable for a multi-level account of intuition and for a fruitful dialogue with distant research areas. It critically discusses two mainstream conceptualizations of intuition which claim to be grounded in a cross-disciplinary consensus. Drawing on the complexity paradigm, it then proposes a conceptualization of intuition as emergence. Finally, it explores the theoretical and practical implications.
Simulation of orbital angular momentum radio communication systems based on partial aperture sampling receiving scheme

The incoherent orbital angular momentum (OAM) radio waves can be used to transmit different information on the same frequency and have a great potential in wireless communication system. However, it needs a large aperture size to receive and demultiplex the orthogonal OAM waves due to the amplitude null in the beam centre and the beam divergence. An improved receiving scheme named partial aperture sampling receiving (PASR) is proposed to solve this problem. The theoretical analysis of PASR is first presented and simulations of OAM radio communication link are carried on to evaluate the performance of PASR. The effects of some non-ideal receiver conditions, e.g. radial deviation and angular deviation on the PASR scheme and the superiority of PASR are explored. These simulated results will give a helpful guide on the manipulation of practical OAM-based wireless communication systems.
Saving Migrants’ Basic Human Rights from Sovereign Rule

States cannot legitimately enforce their borders against migrants if dominant conceptions of sovereignty inform enforcement because these conceptions undermine sufficient respect for migrants’ basic human rights. Instead, such conceptions lead states to assert total control over outsiders’ potential cross-border movements to support their in-group’s self-rule. Thus, although legitimacy requires states to prioritize universal respect for basic human rights, sovereign states today generally fail to do so when it comes to border enforcement. I contend that this enforcement could only be rendered legitimate if it was predicated on more desirable conceptions of sovereignty that supported the universal prioritization of basic human rights. Specifically, desirable conceptions would not establish and require absolute state sovereignty over borders as a necessary precondition for true popular self-governance.
Synthesis of azadiphosphiridine complexes. Theoretical studies on ring formation, the P-to-P' metal shift and the resulting nitrogen geometry.

A set of azadiphosphiridine complexes 3a and 4b,c were synthesized in high selectivity using N-H and P-H deprotonation as key steps and RPCl2 as substrates (R = NiPr2 (a), -tBu (b), Ph (c)). While complex 3a (P-NiPr2) retained the P-W linkage of the starting material W(CO)5{Ph3CP(H)NH}, complexes 4b (P-tBu) and 4c (P-Ph) revealed that a P-to-P' haptotropic shift of the W(CO)5 group has occurred. Remarkably, complex 3a, bearing an unligated P-NiPr2 unit, displays a planar ring N geometry while 4b,c showed a pyramidal geometry of the ring nitrogen atom. Theoretical studies on the ring formation including the P-to-P' haptotropic metal shift and the factors influencing the ring nitrogen geometry are reported.
Three-dimensional structure-based approach for the analysis of macroscopic lead structures on sealing counterfaces

The seal failure of an elastomer rotary shaft seal is often caused due to lead on the shaft counterface. In sealing technology, the term ‘lead’ includes all structures on sealing counterfaces that are capable of transporting fluid in axial direction through the sealing contact and thus disrupting the sealing mechanism. Lead structures are created during the manufacturing process of the shaft surface or throughout the handling. They occur in various shapes and sizes. Depending on the characteristics of the lead structures, several specialized measurement and evaluation methods exist which have to be applied in combination. However, not all types of lead can be covered with the methods known so far. State of the art are frequency-based and model-based analysis methods, which are only able to detect periodic lead structures. Aperiodic and stochastically distributed lead structures cannot be detected due to the functional principle. This article provides an approach for a structure-based evaluation of macroscopic lead structures based on optical topography measurement data. This allows to detect all known types of macroscopic lead on the shaft surface and in future to measure microscopic and macroscopic lead with a single measurement procedure.
Threat-modeling-guided Trust-based Task Offloading for Resource-constrained Internet of Things

There is an increasing demand for Internet of Things (IoT) networks consisting of resource-constrained devices executing increasingly complex applications. Due to these resource constraints, IoT devices will not be able to execute expensive tasks. One solution is to offload expensive tasks to resource-rich edge nodes, which requires a framework that facilitates the selection of suitable edge nodes to perform task offloading. Therefore, in this article, we present a novel trust-model-driven system architecture, based on behavioral evidence, that is suitable for resource-constrained IoT devices and supports computation offloading. We demonstrate the viability of the proposed architecture with an example deployment of the Beta Reputation System trust model on real hardware to capture node behaviors. The open environment of edge-based IoT networks means that threats against edge nodes can lead to deviation from expected behavior. Hence, we perform a threat modeling to identify such threats. The proposed system architecture includes threat handling mechanisms that provide security properties such as confidentiality, authentication, and non-repudiation of messages in required scenarios and operate within the resource constraints. We evaluate the efficacy of the threat handling mechanisms and identify future work for the standards used.
Potential of Integrated Use of Bacillus sp. AZ6
and Organic Waste for Zinc Bio-Activation
to Improve Physiological Attributes of Maize

Zinc (Zn) is an important micronutrient for plant physiology, including the activation of various enzymes, nitrogen metabolism, cell-membrane integrity, and carbonic anhydrase activity. Its deficiency is reported in plants grown in poor soils worldwide including Pakistan. Exogenous application of Zn fertilizers is not efficient due to fixation into the soil. Thus, Zn solubilizing bacteria have a stronger power to chelates the insoluble Zn compounds which may increase Zn availability for plant uptake. Therefore, a pot trial was conducted to evaluate the effects of four products of bio-activated zinc oxide (ZnO) formulated using bio augmented-organic matter coated with zinc oxide (BOZ) on the physiological attributes of maize. Four different products viz. BOZ1, BOZ2, BOZ3, and BOZ4 were prepared using Bacillus sp. AZ6 strain augmented orange peel and ZnO. The results revealed that BOZ4 formulation performed outclass by exhibiting 85%, 31%, and 108% higher photosynthetic rate, stomatal conductance, and transpiration rate, respectively, compared to control. Likewise, it showed a maximum increase in carbonic anhydrase activity, vapor pressure deficit, electrolyte leakage, and SPAD value by 74%, 44%, 45%, and 66%, respectively, over control. Hence, it is concluded that bio-activation of ZnO by Bacillus sp. AZ6 and orange-peel waste could serve as an effective strategy to improve the physiology of maize.
Adoption of Education Technologies for Learning During COVID-19 Pandemic: The Experiences of Marginalized and Vulnerable Learner Populations in Kenya

The onset of COVID-19 made governments and other education actors prioritize distance learning, particularly through education technologies (EdTechs). Most sub-Saharan African countries adopted and adapted this approach. This paper examines the extent of EdTechs’ deployment in Kenya during the COVID-19 pandemic among marginalized and vulnerable populations. A cross-sectional study design was adopted for the study from which this paper drew its data, with both secondary and primary data utilized. The findings show that marginalized/vulnerable learner populations are still left out on EdTech supported learning. This article proposes salient recommendations that could help advance inclusive education discussion and related EdTechs’ discourse.
Interference Effect of Wake Body on the Cross Flow Oscillation of a Square Cylinder in Uniform Flow

Wind tunnel experiments are carried out to investigate interference effect of wake body on cross flow vibration of a square cylinder in uniform flow. The side length d of the square cylinder is 26∼40 mm and the length le = 315 mm. As the wake body, a strip-plate of width w = d is set downstream the square cylinder with a gap s in cruciform arrangement. The length of the plate ld is varied from infinity, i.e. full measuring section height, to ld /d = 1. Both the Karman vortex excitation (K-VIV) and the galloping are suppressed by the ld /d = ∞ plate in the non-dimensional gap range of 1.6<s/d ≦ 4, although the mechanisms are completely different between the two oscillations. The longitudinal vortex excitation (L-VIV) found in the previous work is confirmed to be induced by the plate at around s/d = 1.4 for the systems with various dimensions and structure parameters. The K-VIV suppression effect is virtually the same for the wake plates with ld /d≧10, and becomes less definite for shorter plates when ld /d ≦ 6. The galloping suppression effect persists up to the shortest wake plate of ld /d = 1 at s/d<2. The L-VIV is observed for plates of ld /d≧6, with weaker degree for shorter plates. The K-VIV seems to be enhanced by ld /d = 2, 4, 6 plates at 1≦s/d≦2 (EK-VIV). By setting the wake plate with ld /d = 1 or 2 at s/d around 0.3, a new type of fluid-elastic vibration is induced as an interference effect of wake body (WBI-FEV). A method is presented to predict fluid-elastic vibrations to which the Van der Pol equation does not apply. The prediction by this method agrees well with measured WBI-FEV for the ld /d = 2 plate.Copyright © 2009 by ASME