Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiplexing Capacity of Hybrid PD-SCMA Heterogeneous Networks

Hybrid multiple access schemes are considered potential technologies towards achieving optimal spectrum sharing for future heterogeneous networks. Multiple users are multiplexed on a single resource unit in the code domain for sparse code multiple access (SCMA) or power domain for power domain non-orthogonal multiple access (PD-NOMA) and in both domains for the hybrid power domain sparse code non-orthogonal multiple access (PD-SCMA). This allows for effective spectrum usage but comes at a cost of increased detection complexity resulting in loss of performance in terms of outages. It is therefore imperative to determine the user multiplexing capacity for effective performance. This work investigates codebook capacity bounds in small cells, pairing and power capacity bounds for the number of small cell user equipment’s (SUEs) and macro cell user equipment’s (MUEs) that can be multiplexed on a codebook for the developed PD-SCMA technology. Closed-form solutions for codebook, pairing and power multiplexing capacity bounds are derived. The performance of the system results into low outage when the system’s point of operation is within the multiplexing bounds. To alleviate the resource allocation (RA) challenges of such a system at the transmitter, dual parameter ranking (DPR) and alternate search method (ASM) based RA schemes are proposed. The results show significant capacity gain with DPR-RA in comparison with conventional schemes.
Analysing the effects of knowledge management processes on human resource management practices: a case study on an oil company in the Gulf region

Both knowledge management (KM) and human resource management (HRM) are considered vital components for gaining sustainable competitive advantage in knowledge economies. This study aims to reveal the effects of KM processes on HRM practices by analysing a case study based on data collected from one of the most important energy companies in the Gulf region. According to Forbs Magazine (Helman, 2015), it is considered as one of the leading companies in hydrocarbons exploration, production, refinement, distribution, shipment and marketing, as well as being one of the world's top exporter of crude oil and natural gas liquids (NGLs). The findings indicate that among KM processes, knowledge generation, codification and utilisation have direct impact on HRM practices. Contrastively, knowledge sharing appeared to have no significant effect on HRM practices.
Efficient simulations of stretch growth axon based on improved HH model

ABSTRACT Objective According to recent studies, synaptic connections by axons formed can resist stronger mechanical stresses. A large number of nerve tissues with regular growth can be achieved quickly by appropriately managing the pulling pace and force. However, currently there are few studies on the physiological characteristics of stretching growth axons. Until now, there is no mature technology for determining whether the axons can normally transmit neural signals following continuous mechanical stimulation. In this paper, an improved HH model was proposed to investigate the effect of mechanical stimuli on stretched axons and synapses. Methods First, we add the link between membrane capacitance and diameter to the standard HH model and the fundamental concept of capacitance. Then, unmyelinated stretch growth axons with different lengths were simulated in this model. Results After mechanical pulling stimulation, the improved model successfully replicated the generation and propagation of action potentials in several different axon segments. This increase in length accompanying an increase in diameter due to stretch growth. When the stretching growth axon was stimulated again by traction, the membrane capacitance rapidly increased from the constant value and the inward current was large enough to depolarize the membrane and produce an action potential. After stretching, nerve fibers could still receive signals sent by other neuron cells and complete the signal transmission. Discussion This proposed research can help to optimize stretching axon culture conditions, avoid mechanical force damage to nerve tissue, and achieve a more effective nerve tissue culture process.
Challenges of Large-Scale Multi-Camera Datasets for Driver Monitoring Systems

Tremendous advances in advanced driver assistance systems (ADAS) have been possible thanks to the emergence of deep neural networks (DNN) and Big Data (BD) technologies. Huge volumes of data can be managed and consumed as training material to create DNN models which feed functions such as lane keeping systems (LKS), automated emergency braking (AEB), lane change assistance (LCA), etc. In the ADAS/AD domain, these advances are only possible thanks to the creation and publication of large and complex datasets, which can be used by the scientific community to benchmark and leverage research and development activities. In particular, multi-modal datasets have the potential to feed DNN that fuse information from different sensors or input modalities, producing optimised models that exploit modality redundancy, correlation, complementariness and association. Creating such datasets pose a scientific and engineering challenge. The BD dimensions to cover are volume (large datasets), variety (wide range of scenarios and context), veracity (data labels are verified), visualization (data can be interpreted) and value (data is useful). In this paper, we explore the requirements and technical approach to build a multi-sensor, multi-modal dataset for video-based applications in the ADAS/AD domain. The Driver Monitoring Dataset (DMD) was created and partially released to foster research and development on driver monitoring systems (DMS), as it is a particular sub-case which receives less attention than exterior perception. Details on the preparation, construction, post-processing, labelling and publication of the dataset are presented in this paper, along with the announcement of a subsequent release of DMD material publicly available for the community.
Use of Machine Learning and Routine Laboratory Tests for Diabetes Mellitus Screening

Most patients with diabetes mellitus are asymptomatic, which leads to delayed and more complex treatment. At the same time, most individuals are routinely subjected to standard clinical laboratory examinations, which create large health datasets over a lifetime. Computer processing has been used to search for health anomalies and predict diseases using clinical examinations. This work studied machine learning models to support the screening of diabetes through routine laboratory tests using data from laboratory tests of 62,496 patients. The classification and regression models used were the K-nearest neighbor, support vector machines, Bayes naïve, random forest models, and artificial neural networks. Glycated hemoglobin, a test used for diabetes diagnosis, was used as the target. Regression models calculated glycated hemoglobin directly and were later classified. The performance of classification computer models has been studied under various subdataset partitions and combinations (e.g., healthy, prediabetic, and diabetes, as well as no healthy and no diabetes). The best single performance was achieved with the artificial neural network model when detecting prediabetes or diabetes. The artificial neural network classification model scored 78.1%, 78.7%, and 78.4% for sensitivity, precision, and F1 scores, respectively, when identifying no healthy group. Other models also had good results, depending on what is desired. Machine learning-based models can predict glycated hemoglobin values from routine laboratory tests and can be used as a screening tool to refer a patient for further testing.
Growing Value: Business-University Collaboration for the 21st Century

This is the fourth and final report of the Enhancing Value Task Force. At the beginning of the Task Force, we set out to review and research ways of enhancing the value of universities and the public research base, and to make key recommendations to support value creation. In this report, we draw on our three research reports and extensive consultations with business and academic leaders in particular our Steering and Working Groups. We would like to thank everyone involved in what has been a wide ranging and deep engagement with this most vital of challenges for the UK economy. " Universities are… first and foremost designed to achieve a new understanding of natural phenomena and technologies: in this task they are naturally inventive. Conversely, in modern free market economies, it is firms that have the incentives and governance structures to make innovation their central goal, and are expected to be the almost exclusive sources of innovation. " Foray and Lissoni, Handbook of the Economics of Innovation i " …the issue is not about isolating the impact of publicly-funded research… It is instead about analysing how best to understand and manage connections…between differently funded and motivated research efforts in a system of knowledge production and innovation " Hughes and Martin, The Impact of Public Sector R&D ii " It is the job of universities to 'top up the hopper' of ideas. " iii " Why struggle alone when you can work together? And why not capitalise on the proximity of academia, industry and biotech? " GSK Case study 1 1 See p.34 for GSK case study: Biomedical Cluster
Somatotype of Iranian Soccer Premier League Players

Aim: The aim of the present study was to examine the somatotype of elite soccer players based on positions. A total of 232 elite male soccer players (24.14±5.15) participated in this study. Methods. All anthropometric measurements (10 variables) were performed by a criterion anthropometrists according to the standards of the International Society for Advancement of Kinanthropometry (ISAK). Heath-Carter Somatotyping method was used to calculate endomorphy, mesomorphy and ectomorphy components. Results. The mean body mass and height were 76.29 ± 7.96 kg and 180.42 ± 6.82 cm, while the mean somatotype values were 1.89 ± 0.60 - 4.91 ± 0.80 - 2.65 ± 0.77. Somatotype, height and body mass of the goalkeepers showed a significant difference with the other positions. Conclusion. The findings of this study provide a valuable reference data to support soccer talent identification programs and development of more specific preparatory strategies for soccer.
Patients’ Lived Experiences of the Paternalistic Care Behavior: A Qualitative study

Introduction: The major role of nurses in caring for patients puts them in a position where they can feel a sense of independence or lack of autonomy in dealing with patients throughout their actions. The present study aimed to explain patients’ lived experiences of paternalistic care behaviors. Methods: This qualitative research was conducted with the design of hermeneutic phenomenology consistent with Heidegger’s philosophical view and using the purposeful sampling method. Data richness was achieved after 13 interviews with 7 patients who had been hospitalized and received care in the hospitals of Tehran, Iran. The data were collected during 8 months (November 2020-June 2021) using an unstructured interview and analyzed using Diekelmann et al seven step approach with MAXQDA version 10 software. Results: Data analyses revealed four themes, thirteen sub-themes, and one constitutive pattern (duality of support and suppression of independence) forming the structure of patients’ lived experience of paternalistic caring behaviors. The themes included (1) Support at helplessness, (2) Inflexibility (3) Vague awareness, and (4) Despair due to lack of autonomy. Conclusion: The meanings discovered in this research revealed that patients have dual emotions regarding paternalistic care behavior. On the one hand, they are pleased with the care provided, but on the other hand, they feel desperate and unable to make decisions due to being deprived of their independence. We can see the creation of new ethical values in care behaviors. Performing supportive care behavior with emphasis on patient participation should be considered as a key ethical principle in patient care.
Date-Palm-Derived Cellulose Nanocrystals as Reinforcing Agents for Poly(vinyl alcohol)/Guar-Gum-Based Phase-Separated Composite Films

The current study delineates the use of date-palm-derived cellulose nanocrystals (dp-CNCs) as reinforcing agents. dp-CNCs were incorporated in varying amounts to poly(vinyl alcohol)/guar-gum-based phase-separated composite films. The films were prepared by using the solution casting method, which employed glutaraldehyde as the crosslinking agent. Subsequently, the films were characterized by bright field and polarizing microscopy, UV-Vis spectroscopy, FTIR spectroscopy, and mechanical study. The microscopic techniques suggested that phase-separated films were formed, whose microstructure could be tailored by incorporating dp-CNCs. At higher levels of dp-CNC content, microcracks could be observed in the films. The transparency of the phase-separated films was not significantly altered when the dp-CNC content was on the lower side. FTIR spectroscopy suggested the presence of hydrogen bonding within the phase-separated films. dp-CNCs showed reinforcing effects at the lowest amount, whereas the mechanical properties of the films were compromised at higher dp-CNC content. Moxifloxacin was included in the films to determine the capability of the films as a drug delivery vehicle. It was found that the release of the drug could be tailored by altering the dp-CNC content within the phase-separated films. In gist, the developed dp-CNC-loaded poly(vinyl alcohol)/guar-gum-based phase-separated composite films could be explored as a drug delivery vehicle.
The role of filial piety in career interest alignment, identity alignment, and affective commitment: Evidence from Indonesia

In Indonesia, where most business organizations are family-owned, culture influences family employees’ behavior. Filial piety, or honoring the seniors, is considered a significant cultural value that motivates the family employees to be committed to the business. This study aims to test the effect of filial piety on identity alignment, career interest alignment, and affective commitment. Quantitative analysis is conducted to test the hypotheses of this study using purposive sampling based on questionnaire survey responses from 270 junior family business employees. The study employs Partial Least Square-Structural Equation Modelling (PLS-SEM) analysis with the SmartPLS software to test the hypotheses. The test result shows that: 1) filial piety has a positive effect on identity alignment and career interest alignment, 2) identity alignment has a positive effect on affective commitment, and 3) career interest alignment has a positive effect on affective commitment. The study illustrates how filial piety affects junior family employee behavior, an issue that has not been addressed before in Asian family business studies. Acknowledgment The publication of this study is supported by Indonesia International Institute for Life Sciences (i3L) LPPM fund.
Bayesian Non-linear System Identification and Frequency Response Analysis with Application to Soft Smart Actuators

Newly emerging classes of next generation soft-smart actuators are set to have a huge impact on the fields of robotics, orthotics and prosthetics due to their lightweight, high-strain and muscle-like properties. Like muscle, these actuators can be used in multiple roles, e.g. both as actuators and brakes, due their variable compliance. One important class of soft actuator is the dielectric elastomer actuator (DEA). However, DEAs are extremely difficult to control due to their non-linear and time varying dynamics. A crucial step in the advancement of this technology is the development of techniques for systems level modelling and analysis, which is the focus of this thesis. In the first part of the thesis, a set of DEAs are identified and analysed using standard methods from the field of system identification, obtaining non-linear autoregressive with exogenous input (NARX) models. These provide a benchmark against which later methods are evaluated. The key novelty in this part is the development of NARX models of DEAs for use in non-linear frequency-domain analysis. This result provides insight for the first time into how a set of similarly fabricated DEAs vary in different ways. A further aspect of DEA behaviour is their unexplained time varying behaviour. The system identification approach used to identify NARX models of DEAs is in a convenient form such that it can be easily extended to cater for this time varying behaviour. There are however very few available methods for the frequency domain analysis of time varying systems. A novel method for time varying frequency domain analysis of NARX systems is developed in this work and applied to the DEAs. The analysis procedure is used to provide insight on how the dynamic behaviour of DEAs change over time. In the second part of the thesis a novel approach to the joint structure detection and parameter estimation of NARX models is developed using a sparse Bayesian method. The Bayesian framework allows for the estimation of posterior distributions over model parameters, characterising the model uncertainty. Analytic solutions are found that describe model uncertainty in the frequency-domain as confidence bounds on both linear and higher order frequency response functions. The sparse Bayesian identification algorithm is applied to the DEA data sets and is used to give the first non-linear dynamic model of DEAs with uncertainty bounds plus the first description of DEA dynamics in the frequency-domain, again with uncertainty bounds.
Industrial Heritage: In-Between Memory and Transformation

Exploratory Research into Transformation Processes of Former Industrial Complexes of Leipziger Baumwollspinnerei (Leipzig) and Mattatoio di Testaccio (Rome); New Meanings of Industrial Heritage Physical manifestations of the Industrial Revolution left a permanent imprint on the complexion of cities. Abandonment that followed the deindustrialization contributed to an estrangement, turning derelict industrial spaces and run‐down factories into a ballast to conjure with. At present, industrial heritage management applies flexibility and creativity, partially overcoming the essentially traditional paradigm of heritage preservation. This approach permits sustainable conservation – utilization and integration of disused industrial constructs in the contemporary urban landscape. Being a part of the European cultural stock, industrial heritage is an exciting and unique setting from many perspectives. It is defined and consumed by many markets, ranging from the industrial heritage tourism to the market of special events and festivals. Reused industrial buildings and factories come into view as products of post‐industrial societies, fitting to the Western post‐industrial (consumer) culture, offering a field of activities that are at an interface between the industrial history and contemporary socio‐cultural milieu. Alteration of values, growth of new roles and definitions of industrial heritage, generated by functional restructuring, is a subject which is often left behind the general discussion about sustainable conservation and adaptive reuse of industrial heritage. Yet, in the modified state, industrial heritage is very complex to understand and to define. By conducting a desk and a case study research of former industrial complexes – Leipziger Baumwollspinnerei and Mattatoio di Testaccio, this doctoral thesis aims to identify industrial heritage as a contemporary (post‐industrial) concept. Observation of ideas, values and definitions that emerge as a consequence of the transformation and re‐conceptualization of industrial heritage are intended to raise awareness and appreciation of industrial heritage in the full richness of its contemporary interpretation.
Effects of a Postural Exercise Program on Vertical Jump Height in Young Female Volleyball Players with Knee Valgus

Background: Although a knee valgus position is related to the increase in injury risk in volleyball players, there is a lack of studies on the relationship between knee valgus and vertical jump (VJ) performance. Hence, the aim of this study was to investigate the effects of a postural exercise program on VJ height in young female volleyball players with knee valgus. Methods: This pilot study included 19 young female volleyball players divided into the following groups: the Valgus Experimental Group (VEG); the Valgus Control Group (VCG); and the Neutral Control Group (NCG). All three groups carried out the same volleyball training program. In addition, only the VEG underwent a 3-month postural exercise program of 30–45 min/session, twice/week. VJ performance was measured through the Sargent test before (T0), at 6 weeks (T1), and at 12 weeks (T2). Results: A significant effect from T0 to T1 (p = 0.0017) and from T0 to T2 (p = 0.0001) was found in the VEG. No significant differences were found over time in the VCG and in the NCG. Conclusion: An integrated postural exercise program might lead to a more balanced muscle efficiency inducing athletes to obtain a higher VJ performance.
NETWORK FOR A EUROPEAN FOREST INFORMATION SERVICE (NEFIS) - ESTABLISHMENT OF A KNOWLEDGE BASE

The project 'Network for a Forest Information Service' (NEFIS; contract number QLK5-CT-2002-30638) is an 'Accompanying Measure' of the European Commission (EC) 5 th Framework Programme. A central component of the project is the establishment of a Web-based KnowledgeBase with substantive structured information content. The KnowledgeBase of NEFIS includes a repository of metadata and controlled vocabulary standards, software design documents, comprehensive frequently asked questions, worked examples and software distributions. Its content is based on essential documentation of activities related to forest information systems. NEFIS originates from the Council Regulation (1989, (EC) No 1615/89 and its extension as of 1998; 1998-2002) aiming to elaborate a European Forest Information and Communication System. A Web- based demonstration tool of such a system was built within a preceding project (European Forest Information System - EFIS; contract number 17186-2000-12 F1ED). NEFIS is taking the development of the tool further by seeking coordination of ongoing efforts to create forest information systems and services at the European level. Further it seeks options to support potential data providers at various spatial (international, national, sub- national) levels to develop harmonized standards and procedures for providing actual data and elaborate metadata. The project has close cooperation with the Global Forest Information Service initiative. This paper will concentrate on giving insight into the establishment of the KnowledgeBase.
Design of Multi-Channel Wireless Sensor Networks Based On Compressive Sensing Theory and Spectrum Sensing Theory

The single-channel wireless sensor networks (WSNs) exists the problem of low efficiency of monitoring data transmission, however the multi-channel WSNs exists the problem of communication collision caused by the sensor node’s wireless channel competition. The paper at first introduces the causes of the above problems and selects a reasonable wireless channel resources allocation method of the multi-channel WSNs. Then to solve these questions, the theory of compressive sensing and spectrum sensing are adopted to improve the existing multi-channel WSNs. Finally, a new sensor node of the multi-channel WSNs is designed based on the above improvement. By analyzing the monitoring data of the field test, the improved multi-channel WSNs could complete monitoring mission efficiently and accurately, meanwhile it reduced power consumption of the WSNs effectively.