Miracle-dz/UniFAR-FTUs huggingface dataset:
An Open Source Multi-Slice Cell Capacity Framework

5G is the new 3GPP technology designed to solve a wide range of requirements. On the one hand, it must be able to support high bit rates and ultra-low latency services, and on the other hand, it should be able to connect a massive amount of devices with loose bandwidth and delay requirements. Network Slicing is a key paradigm in 5G, and future 6G networks will inherit it for the concurrent provisioning of diverse quality of service. As scheduling is always a delicate vendor topic and there are not so many free and complete simulation tools to support all 5G features, in this paper, we present Py5cheSim. Py5cheSim is a flexible and open-source simulator based on Python and specially oriented to simulate cell capacity in 3GPP 5G networks and beyond. To the best of our knowledge, Py5cheSim is the first simulator that supports Network Slicing at the Radio Access Network. It offers an environment that allows the development of new scheduling algorithms in a researcher-friendly way without detailed knowledge of the core of the tool. The present work describes its design and implementation choices, the validation process and results, and different use cases.
“You Have to Go Gently”: Mentors’ Perspectives of a Peer Mentoring Empowerment Program to Reduce Marginalization in Refugee and Migrant Women

The Empowerment and Peer Mentoring of Migrant and Refugee Women pilot program (EMPOWER) provides a mechanism for migrant women who have established lives in Australia to mentor newly arrived women to build the ability, confidence, and knowledge to overcome barriers to the social determinants of health such as employment. Female migrant mentors (n = 21) met with their mentees (n = 32) on a regular basis over a period of 3 to 12 months between September 2019 and November 2021. The individual mentoring was augmented by group workshops facilitated by content experts and the research team. The unique perspectives of the mentors were explored through individual interviews (n = 15) and analysis of journal entries (n = 58) submitted regularly by mentors throughout the program. Thematic analysis revealed that mentors were intrinsically motivated to build strong and trusting connections with their mentees, which were pivotal to reducing inequalities for mentees and their families. Mentors had high expectations of themselves and demonstrated commitment and flexibility to accommodate mentees’ needs. However, they sometimes struggled when supporting mentees who were overwhelmed by the systemic and other stressors associated with resettlement and pre-migration trauma. Regular networking and moral support for mentors would enhance future programs.
Inverter Based DGs for Power Quality Enhancement and Protection in Distribution Network

In this paper, a new three-phase wind energy inverter (WEI) with flexible AC transmission system (FACTS) capability is presented. The proposed inverter is placed between the wind turbine and the grid, same as a regular WEI, and is able to regulate reactive power transferred to the grid. The goal of this paper is to introduce new ways to increase the penetration of renewable energy systems into the distribution systems. This will encourage the utilities and customers to act not only as a consumer, but also as a supplier of energy. Moreover, using the new types of converters with FACTS capabilities will significantly reduce the total cost of the renewable energy application. In this paper, modular multilevel converter is used as the desired topology to meet all the requirements of a three-phase system such as efficiency, and total cost of the system. The simulations for an 13-level inverter have been done in MATLAB/Simulink.
Construction of Enterprise Financial Early Warning Model Based on Logistic Regression and BP Neural Network

At present, the number of enterprises in financial crisis in China is rising sharply, and the ability of enterprises to resist risks is generally weak. Therefore, it is necessary to establish a corporate financial crisis early warning system, to detect the signs of corporate financial crisis before it arrives and to inform managers in advance, so that effective measures can be taken as soon as possible to eliminate hidden dangers. This paper selects the two-year data of 40 companies from 2017 to 2019 as training samples and the data of 20 companies as prediction samples. After testing, 12 index variables that can reflect the financial problems of energy companies are finally selected as the basis for modeling. Then, we use Logistic and BP neural network modeling, respectively, to study and compare the data from 2017 to 2019 to predict the financial risk in the following year. The results show that the BP neural network model in the two models is better than the Logistic model in terms of fitting degree or prediction accuracy for enterprise financial early warning. Therefore, the BP neural network model has a better effect and is more suitable for the practical application of enterprises in China.
Cell–Cell Contact Mediates Gene Expression and Fate Choice of Human Neural Stem/Progenitor Cells

Transplantation of Neural Stem/Progenitor Cells (NPCs) is a promising regenerative strategy to promote neural repair following injury and degeneration because of the ability of these cells to proliferate, migrate, and integrate with the host tissue. Precise in vitro control of NPC proliferation without compromising multipotency and differentiation ability is critical in stem cell maintenance. This idea was highlighted in recent clinical trials, where discrepancies in NPC culturing protocols produced inconsistent therapeutic benefits. Of note, cell density plays an important role in regulating the survival, proliferation, differentiation, and fate choice of stem cells. To determine the extent of variability produced by inconsistent culturing densities, the present study cultured human-induced pluripotent NPCs (hiPSC-NPCs) at either a low or high plating density. hiPSC-NPCs were then isolated for transcriptomic analysis or differentiation in vitro. Following sequencing analysis, genes involved in cell–cell contact-mediated pathways, including Hippo-signaling, NOTCH, and WNT were differentially expressed. Modulation of these pathways was highly associated with the regulation of pro-neuronal transcription factors, which were also upregulated in response to higher-density hiPSC-NPC culture. Moreover, higher plating density translated into a greater neuronal and less astrocytic differentiation in vitro. This study highlights the importance of precisely controlling culture conditions during the development of NPC transplantation therapies.
Phenological patterns of herbaceous Mediterranean plant communities in spring: is there a difference between native and formerly-cultivated grasslands?

Background and aims – Plant phenology, defined as the timing of recurring life events like leaf flushing, flowering, or fruiting, is highly sensitive to environmental factors such as photoperiod, temperature, and moisture. Phenological synchrony between interacting species – such as plants and their pollinators – is of major importance to the structure and functioning of ecosystems. Plant phenology might also be affected by changes in edaphic conditions. However, whether former agricultural activities may shift phenological patterns of plant communities remains poorly understood. In this study, we evaluated the impact of past agricultural practices on herbaceous plant community phenology in the protected Mediterranean xeric grassland of La Crau (France). Material and methods – We compared (1) species composition, and (2) phenological patterns of annuals, perennials, Bromus rubens (annual), and Lobularia maritima (perennial), in formerly-cultivated plots – abandoned for 30 years – and intact native grassland plots (steppe), both subjected to itinerant sheep grazing. Key results and conclusion – Our results suggest that former agricultural activities can affect species composition of Mediterranean xeric grassland communities with differences visible after 30 years of abandonment, but only altered phenological patterns slightly. We suggest that climatic factors and sheep grazing acted as strong habitat filters constraining community assembly at the phenological level.
Human Activity Recognition using Motion History Algorithm

In this research, I have worked to recognize various human actions and activities using Motion History Algorithm. Firstly, I studied different techniques already implemented by various researchers in this field like motion image energy etc and finally develop an approach. In this approach, videos are converted into image frames and the images are pre-processed plus background subtraction is computed for these frames. Then, the motion history of images is computed, and features are extracted. After that, Discrete Cosine Transform (DCT) of the Region of Interest is computed which is then thresholded for classification. The proposed algorithm is able to distinguish between various human actions sittings, standing, hand waving etc. 1.1. Overview: Since the demands of the applications are increasing on daily basis therefore automatically recognition of human activities is in our sights. In surveillance environment, the detection of not normal activities will be very helpful in production of alerts for potential crime. In entertainment environment, this recognition will update the human computer interaction (HCI). In healthcare system, recognition of activities will provide help the rehabilitation of patients. Generally, recognition of human activities is divided into two levels of representations as shown in figure 1: 1. Low-level core technology. 2. High-level applications. In core technology, there are 3 main stages for processing any activity. These stages are object segmentation, feature extraction and classification algorithms. First of all human object in a video sequence will be segmented out. The main characteristics are carefully extracted and the properly represented by labels or features such as: • Shape. • Silhouette. • Colors. • Poses. • Body motions. So in a nut shell, once the features are extracted, the algorithms are applied for the detection, recognition and classification of human activities. High level of applications only works on the results which are obtained when the algorithm are successfully applied on surveillance environments, entertainment environments or healthcare systems.
Asymmetry bistability for a coupled dielectric elastomer minimum energy structure

In this paper, a novel design of asymmetry bistability for a coupled dielectric elastomer minimum energy structure (DEMES) is presented. The structure can be stable both in the stretched and curved configurations, which are induced by the geometry coupling effect of two DEMESs with perpendicular bending axes. The unique asymmetry bistability and fully flexible compact design of the coupled DEMES can enrich the active morphing modes of the dielectric elastomer actuators. A theoretical model of the system’s strain energy is established to explain the bistability. Furthermore, a prototype is fabricated to verify the conceptual design. The experimental results show that when the applied voltage is below a critical transition one, the structure behaves as a conventional DEMES, once the applied voltage exceeds the critical voltage, the structure could change from the stretched (curved) configuration to the curved (stretched) configuration abruptly and maintain in a new stable configuration when the voltage is removed. A multi-segment structure with the coupled DEMES is also presented and fabricated, and it displays various voltage-actuated morphings. It indicates that the coupled DEMES and the multi-segment structures can be useful for the soft and shape-shifting robots.
State of the Art of Chemosensors in a Biomedical Context

Healthcare is undergoing large transformations, and it is imperative to leverage new technologies to support the advent of personalized medicine and disease prevention. It is now well accepted that the levels of certain biological molecules found in blood and other bodily fluids, as well as in exhaled breath, are an indication of the onset of many human diseases and reflect the health status of the person. Blood, urine, sweat, or saliva biomarkers can therefore serve in early diagnosis of diseases such as cancer, but also in monitoring disease progression, detecting metabolic disfunctions, and predicting response to a given therapy. For most point-of-care sensors, the requirement that patients themselves can use and apply them is crucial not only regarding the diagnostic part, but also at the sample collection level. This has stimulated the development of such diagnostic approaches for the non-invasive analysis of disease-relevant analytes. Considering these timely efforts, this review article focuses on novel, sensitive, and selective sensing systems for the detection of different endogenous target biomarkers in bodily fluids as well as in exhaled breath, which are associated with human diseases.
Happy Birthday? Relative Age Benefits and Decrements on the Rocky Road

(1) Background: There is abundant literature in talent development investigating the relative age effect in talent systems. There is also growing recognition of the reversal of relative age advantage, a phenomenon that sees significantly higher numbers of earlier born players leaving talent systems before the elite level. However, there has been little investigation of the mechanisms that underpin relative age, or advantage reversal. This paper aimed to investigate (a) the lived experience of relative age in talent development (TD) systems, (b) compare the experience of early and late born players, and (c) explore mechanisms influencing individual experiences. (2) Methods: interviews were conducted with a cohort of near elite and elite rugby union players. Data were subsequently analysed using reflexive thematic analysis and findings considered in light of eventual career status. (3) Results: challenge was an ever-present feature of all players journeys, especially at the point of transition to senior rugby. Psycho-behavioural factors seemed to be a primary mediator of the response to challenge. (4) Conclusions: a rethink of approach to the relative age effect is warranted, whilst further investigations of mechanisms are necessary. Relative age appears to be a population-level effect, driven by challenge dynamics.
Talent Management in Hungary. An Empirical Study and Suggestion for a Process-Based Approach

This research aimed to examine the status quo of talent management (TM) in Hungary through an online questionnaire. According to responding companies (n=75), talented employees are interpreted fully/partially by some competencies. The need for talent segmentation seemed to be significant – mainly concentrating on employees with critical skills, graduate/ Gen Z talents, high potentials, managerial talents, and trainee talents. Related to the TM, the respondents’ approaches varied, but four processes typically appeared as components of TM practices – attraction, selection, development, and retention. All of them turned out to be very important, but the respondents experienced difficulties related to each process. Based on the findings, the implementation of a process-based TM model has been proposed. The model suggests interpreting so-called talent potentials, who participate in the entire TM process, along with Spencer and Spencer’s (1993) competency clusters, through which they become the members of particular talent segments.
Estimation of Elbow Wall Thinning Using Ensemble-Averaged Mel-Spectrogram with ResNet-like Architecture

An elbow wall thinning diagnosis method by highlighting the stationary characteristics of the operating loop is proposed. The accelerations of curved pipe surfaces were measured in a closed test loop operating at a constant pump rpm, combined with curved pipe specimens with artificial wall thinning. The vibration characteristics of wall-thinned elbows were extracted by using a mel-spectrogram in which modal characteristic variation shifting can be expressed. To reduce the deviation of the model’s prediction values, the ensemble mean value of the mel-spectrogram was used to emphasize stationary signals and reduce noise signals. A convolutional neural network (CNN) regression model with residual blocks was proposed and showed improved performance compared to the models without the residual block. The proposed regression model predicted the thinning thickness of the elbow excluded in training dataset.
Canadian Journal of Learning and Technology Volume 30(2) Spring / printemps 2004 Planning for Integrating Teaching Technologies

Teaching technologies offer pedagogical advantages which vary with specific contexts. Successfully integrating them hinges on clearly identifying pedagogical goals, then planning for the many decisions that technological change demands. In examining different ways of organizing this process, we have applied planning tools from other domains - Fault Tree Analysis and Capability Maturity Modeling- at the school and college levels. In another approach, we have examined attempts to broadly model the integration process at the university level. Our studies demonstrate that the use of a variety of tools and techniques can render the integration of teaching technologies more systematic.
A novel method for steel bar all-stage pitting corrosion monitoring using the feature-level fusion of ultrasonic direct waves and coda waves

Corrosion monitoring of steel bars has drawn extensive attention in recent decades. Conventional ultrasonic method, utilizing direct waves to detect damage, is adequate for severe pitting corrosion but suffers from low sensitivity to incipient pitting corrosion. Coda wave technique, a very sensitive method to subtle changes in medium using later arrival wave packets, is innovatively introduced to monitor pitting corrosion of steel bars, especially in the early stages. The decorrelation coefficient (DC) values are calculated to quantify the variations of both direct waves and coda waves. To overcome the limitations of coda waves for severe pitting corrosion and remedy the low sensitivity of direct waves for incipient pitting corrosion, a feature-level data fusion strategy is proposed to integrate the two probing waves to monitor all-stage pitting corrosion of steel bars. The combination of direct waves and coda waves could exploit the complementary merits in various pitting corrosion configurations. The proposed feature-level fusion strategy of ultrasonic coda waves and direct waves intercepted from the same recorded signals opens a new perspective in all-stage pitting corrosion monitoring of steel bars and contributes a novel scheme for whole-process damage evaluation of structures.
Employee psychological conditions as mediators of the relationship between human resource management and employee work engagement

Abstract Employee work engagement is an asset valued by today’s organisations, not only as an indicator of well-being at work but also because it improves both employees’ work performance and organisational performance. Knowing how employee work engagement can be fostered in the firm is therefore a subject of great interest to both academics and managers, but few studies have examined how organisational interventions positively affect employee work engagement. In this research, we focus on the relevance of organisations’ human resource management to promote high levels of engagement among their employees. The theoretical framework guiding our research, Kahn’s (1990) model, provides interesting insights into the mechanisms through which human resource management influences employee work engagement. By testing a multilevel model based on matched data from a sample of 146 HR managers and 504 employees in Spanish companies, our analyses show that high performance work systems have a positive influence on work engagement through the employee psychological conditions of meaningfulness, psychological safety and psychological availability.
The Comprehensibility of a Z Specification Language and Its Implementation in JAVA for Implementing Atomic Read/Write Shared Memory in Mobile Ad hoc Network

Comprehensibility is often raised as a problem with formal notations; yet formal methods practitioners dispute this. In a survey, one interview said "formal specifications are no more difficult to understand than code". Measurement of comprehension is necessarily. In this paper, a comprehension of Z specification with that of its implementation in JAVA for atomic object Read/Write shared memory in mobile ad hoc network is performed.
New Metallophthalocyanines Bearing 2-Methylimidazole Moieties—Potential Photosensitizers against Staphylococcus aureus

Newly developed tetra- and octasubstituted methimazole-phthalocyanine conjugates as potential photosensitizers have been obtained. Synthesized intermediates and final products were characterized by the MALD-TOF technique and various NMR techniques, including 2D methods. Single-crystal X-ray diffraction was used to determine the crystal structures of dinitriles. The studied phthalocyanines revealed two typical absorption bands—the Soret band and the Q band. The most intense fluorescence was observed for octasubstituted magnesium(II) phthalocyanine in DMF (ΦFL = 0.022). The best singlet oxygen generators were octasubstituted magnesium(II) and zinc(II) phthalocyanines (Φ∆ 0.56 and 0.81, respectively). The studied compounds presented quantum yields of photodegradation at the level between 10−5 and 10−6. Due to their low solubility in a water environment, the liposomal formulations were prepared. Within the studied group, octasubstituted zinc(II) phthalocyanine at the concentration of 100 µM activated with red light showed the highest antibacterial activity against S. aureus equal to a 5.68 log reduction of bacterial growth.
Large-Scale Analysis of X Inactivation Variations between Primed and Naïve Human Embryonic Stem Cells

X chromosome inactivation is a mammalian dosage compensation mechanism, where one of two X chromosomes is randomly inactivated in female cells. Previous studies have suggested that primed human embryonic stem cells (hESCs) maintain an eroded state of the X chromosome and do not express XIST, while in naïve transition, both XIST and the eroded X chromosome are reactivated. However, the pattern of chromosome X reactivation in naïve hESCs remains mainly unknown. In this study, we examine the variations in the status of X chromosome between primed and naïve hESCs by analyzing RNA sequencing samples from different studies. We show that most samples of naïve hESCs indeed reactivate XIST and there is an increase in gene expression levels on chromosome X. However, most of the naïve samples do not fully activate chromosome X in a uniform manner and present a distinct eroded pattern, probably as a result of XIST reactivation and initiation of re-inactivation of chromosome X. This large-scale analysis provides a higher-resolution description of the changes occurring in chromosome X during primed-to-naïve transition and emphasizes the importance of taking these variations into consideration when studying X inactivation in embryonic development.