Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Method in Pilot Reuse Factor Selection in Spectrum Efficient Massive MIMO Systems

Spectrum efficiency studies of Massive MIMO systems have continued and still have not been fully explored in the literature. Therefore, the spectrum efficiency definition of a particular user in a cell in a Massive MIMO network is expressed in this paper. In addition, the uplink spectrum efficiency expressions for the Rayleigh fading are included. The Monte Carlo simulations are performed to verify these expressions. Due to the expectation of reaching to a thousand antennas together with the millimetre wave structure in the next years, in this study, it is contributed to the literature by explaining how to select the pilot reuse factor. The realization of this contribution is based on Zero Forcing (ZF) and Maximum Ratio Combining (MRC) schemes. The results of this study are useful for optimal design conditions, such as the number of antennas on the base station and pilot reuse factor selection for the next generation networks in order to obtain spectrum efficiency in Massive MIMO systems.
Mission Profile-Based System-Level Reliability Prediction Method for Modular Multilevel Converters

This article proposes a mission profile-based reliability prediction method for modular multilevel converters (MMCs). It includes key modeling steps, such as long-term mission profile, analytical power loss models, system-level and component-level thermal modeling, lifetime modeling, Monte Carlo analysis, and redundancy analysis. Thermal couplings and uneven thermal stresses among submodules are considered. A case study of a 15-kVA down-scale MMC has been used to demonstrate the proposed method and validate the theoretical analysis. The outcomes serve as a first step for developing realistic reliability analysis and model-based design methods for full-scale MMCs in practical applications.
Impact of risks in foodgrains transportation system: a system dynamics approach

The purpose of this paper is to model dynamic feedback effects and complex interactions among risks affecting foodgrains transportation using a system dynamics approach. The risk scenario is simulated using a system dynamics model considering risk index values. It has been observed that there is a significant increase in inventory level from 8.39% to 28.4% and vehicle capacity from 8.99% to 28.4% with a change in risk value by 30%. This can help managers to develop inventory and transportation policies. It will, therefore, help to generate risk reduction scenarios for better availability of foodgrains through integrated risk control and mitigation in a supply chain. The key findings drawn for transportation and inventory management of foodgrains will help policy-makers to improve the efficiency of foodgrains supply chain. This research uniquely analyses the dynamic implication of inventory-transportation policies on foodgrains transportation system using system dynamics modelling approach.
Knowledge, Attitudes and Practices of Mothers Regarding Breastfeeding in the University Hospital Center of Brazzaville (Republic of Congo)

Objective: To analyze the knowledge, attitudes and practices of mothers about breastfeeding at the Brazzaville University Hospital Center. Population and Methods: Analytical KAP study, conducted from February 1 to May 31, 2019, including exclusively manner mothers who have started breastfeeding for at least 4 months and at most 24 months in accordance with the recommendations of the World Health Organization. The study variables were related to socio-demographic characteristics, knowledge, attitudes and practices. Results: One hundred and forty mothers were questioned. They were of a median age of 30, multiparous (61.5%), in a couple (78.6%), with gainful activity (47.9%). They had enough knowledge (87.1%) but harmful in 26.5% of cases, adapted attitudes (95%) with answers of different certainties, and bad practices (60%). Knowledge did not influence attitudes (p > 0.2). Knowledge and attitudes influenced practices (p < 0.05). Women with insufficient knowledge were 4 times more likely to have poor practices (OR = 3.84; CI [1.06 - 13.9]; p < 0.03). Conclusion: An educational strategy on mothers’ knowledge and attitudes towards breastfeeding would help improve their breastfeeding practices.
Social dimension activates the usage and academic impact of Open Access publications in Andean countries: a structural modeling-based approach

Most of the altmetric research in developing countries is descriptive and has not tested models exploring relationships among article-level factors. Therefore, there is a knowledge gap on this issue. The research question for this study was the following: Social dimension is the factor that activates the usage and citation of Open Access publications in Andean countries. DOIs of Andean countries publications in PLoS journals were downloaded using (n = 3,186) using rplos, an Application Programming Interface (API) developed for R: Bolivia (n = 121), Chile (n = 1,180), Colombia (n = 826), Ecuador (n = 266), Peru (n = 622), and Venezuela (n = 171). Data modeling was carried out with Partial Least Squares – Structural Equation Modeling (PLS-SEM). The hypothesized structural model accounted for at least 41% of the explained variance of citations (R2 = 0.406). Among the two associated factors, the usage made the highest contribution (at least 0.639), while the social media showed a negative contribution. The application of PLS-SEM for modeling the information-seeking behavior, at the document level, highlights the positive evidence for the path social → usage → citation, but a negative and nonsignificant association between the social dimension and citation.
Current diagnosis and treatment of carotid atherosclerotic disease

Carotid atherosclerotic disease increases the risk for ischemic stroke and transient ischemic attack and challenges are presented when seeking the appropriate strategy of management. In this review, we will discuss the current diagnostic and treatment approaches of asymptomatic and symptomatic carotid stenosis (SCS). The definition of carotid plaques, staging of stenotic severity, and noninvasive tests including carotid duplex ultrasound, computed tomographic angiography, magnetic resonance angiography, and transcranial Doppler will be summarized. Optimal management for asymptomatic and SCS with medical therapy, carotid artery stenting, or carotid endarterectomy has been controversial and should be judged in specific clinical settings. More clinical data are needed to better understand the correlation of different diagnostic measures and the disease progress and to optimize the treatment approach to improve patient outcomes.
Theory construction in the psychopathology domain: A multiphase approach

Our understanding of mental disorders is facilitated by our theoretical explanations of them. At present, these explanations are practically and theoretically insufficient; possessing widespread conceptual issues (e.g., lack of richness and specificity) and producing therapeutic treatments that lack effectiveness. In our view, one reason for such issues is that we are currently without a systematic method for the construction of these explanations. We therefore present to the reader the Phenomena Detection Method for Theory Construction (PDM-TC), a preliminary systematic framework for the construction of psychopathological explanation comprising three phases: (a) selecting an appropriate explanatory target, (b) developing a rich compositional description, and (c) developing a quality etiological explanation. Using theories of eating disorders as a sustained example, we demonstrate how current explanations of psychopathology execute the tasks associated with each of these phases insufficiently and how the conceptual issues they evidence can be ameliorated by the PDM-TC framework.
Are executive directors paid enough? Evidence from conflicting related-party transactions

This study examines the association between types (packages) of executive director’s remuneration and conflicting related-party transactions (RPT-conflict) among listed companies in Malaysia. The hypotheses are analyzed using a sample of 539 listed companies in Malaysia over the period 2012-2014 with 1,615 observations. The results show that salary (cash-based) and in-kinds remuneration pay to executive director are effective at reducing firm’s engagement in RPT-conflict but an executive director fee alone is not attractive enough. The executive directors favor for the combination of remuneration packages, either involving salary and fee, or salary and in-kinds. This study contributes a greater understanding about the effectiveness of different types of executive director’s compensation to minimize the firm’s engagement with related parties. Additionally, the combination of remuneration package is more attractive and effective at minimizing RPTconflict than individual payment of director fee or salary. The evidence also contributes to the literature by indicating a compensating relationship between each type of executive director’s remuneration and RPT-conflict. The regulators and policy makers, specifically the remuneration committee must concern and seriously consider about the importance relationship between an attractive director’s remuneration and RPTs, and thus, takes the right steps to minimize the expropriation risk. JEL Classification: M41, M52
Parameter-Free Learning for Evolving Markov Decision Processes: The Blessing of (More) Optimism.

We consider un-discounted reinforcement learning (RL) in Markov decision processes (MDPs) under drifting non-stationarity, i.e., both the reward and state transition distributions are allowed to evolve over time, as long as their respective total variations, quantified by suitable metrics, do not exceed certain \emph{variation budgets}. We first develop the Sliding Window Upper-Confidence bound for Reinforcement Learning with Confidence Widening (\texttt{SWUCRL2-CW}) algorithm, and establish its dynamic regret bound when the variation budgets are known. In addition, we propose the Bandit-over-Reinforcement Learning (\texttt{BORL}) algorithm to adaptively tune the \sw~to achieve the same dynamic regret bound, but in a \emph{parameter-free} manner, i.e., without knowing the variation budgets. Notably, learning drifting MDPs via conventional optimistic exploration presents a unique challenge absent in existing (non-stationary) bandit learning settings. We overcome the challenge by a novel confidence widening technique that incorporates additional optimism.
Effects of working years in cold environment on the musculoskeletal system and carpal tunnel symptoms.

OBJECTIVES Musculoskeletal disorders are the most common work-related health problems. The risk of musculoskeletal disorders is increased by working in a cold environment. The present study aims to investigate the effects of working years on the body. METHODS We examined the effects of the working years on the musculoskeletal system and carpal tunnel syndrome symptoms of the individuals who were engaged in cutting, shredding, packaging, bagging and transportation operations at 9 degrees and lower ambient temperatures in a poultry factory in Turkey. Nordic Musculoskeletal Questionnaire (NMQ) was used to evaluate musculoskeletal symptoms of the individuals. Boston Carpal Tunnel Syndrome Questionnaire (BCTQ) was used to investigate the carpal tunnel symptoms. Individuals grouped according to their total working years in a cold factory setting. Groups were formed as less than two years, between two and five years, between six and nine years, and ten years or more. RESULTS This study showed that the increase in working years in a cold factory setting might lead to a feeling of pain and discomfort in various regions of the body, disrupt ordinary works due to the pain felt (p<0.05). This study also showed that the severity of the symptoms felt because carpal tunnel syndrome worsened, especially when an individual has been working for more than ten years in cold. CONCLUSION Working in the cold for a long time may result in long-term health effects on the human body.
Delay Aware Flow Scheduling for Time Sensitive Fronthaul Networks in Centralized Radio Access Network

Packet-based fronthaul (FH) transport networks are promising for future centralized radio access networks (C-RANs), which support statistical multiplexing via flow scheduling. With stringent requirements on FH delay, the FH network is time sensitive. Targeting to minimize the maximum FH delay of all packets, this paper investigates the optimized flow scheduling in the packet-based FH network. Due to the high complexity of optimal solutions, a heuristic higher rate flow scheduled later (HRSL) scheme is proposed to achieve good performance with a low complexity. The main idea is to schedule the higher-rated flow with a lower priority, because packets in the higher-rated flow have a larger solution space to be scheduled with a smaller delay. It is proved that using HRSL, each packet must have a transmission position and no packet will be discarded during scheduling. Moreover, the asymptotic delay of HRSL is derived when the number of flows is sufficiently large. We show that the delay performance of HRSL approaches to the optimal one and yields a reduction of up to 92.6% compared to existing schemes. The properties of HRSL are also verified via simulations. If the required delay is larger than the asymptotic delay performance, the FH network with HRSL can always deliver packets in time, no matter how many flows are scheduled and what the rates of flows are.
Smart Building Temperature Monitoring System using Matplotlib

Wireless sensor network (WSN) has been widely adopted by applications of Internet of Things (IoT). In this paper, we present a practical design of real time temperature monitoring system for smart building by using XBee based mesh WSN. The proposed system collects temperature data from wireless sensors and dynamically displays those data using Matplotlib with Python. The data was recorded by the SQLite3 database simultaneously for cloud usage. Moreover, we evaluated the link quality of the wireless transmission in our system. Experimental results demonstrated that the proposed real time smart building temperature monitoring system is a cross-platform and low cost system for IoT applications. It could be easily applied to single board computer systems such as Raspberry Pi, Jetson Nano, or LatteePanda to further reduce the cost.
Strong flux pinning by columnar defects with directionally dependent morphologies in GdBCO-coated conductors irradiated with 80 MeV Xe ions

We show that Xe ion irradiation with 80 MeV to GdBa2Cu3Oy-coated conductors creates different morphologies of columnar defects (CDs) depending on the irradiation angles θi relative to the c-axis: continuous CDs with a larger diameter are formed for oblique irradiation at θi = 45°, whereas the same ion beam at a different angle (θi = 0°) induces the formation of discontinuous CDs. The direction-dependent morphologies of CDs significantly affect the angular behavior of the critical current density Jc. In particular, low-energy irradiation defects induce further improvement of Jc in a unique combination of irradiation angles of θi = 0° and ±45°: discontinuous CDs at θi = 0° and crossed CDs at θi = ±45° provide correlated pinning in a wide angular range, which is more strongly enhanced by each other via the pinning of kinks.
Modelling thalamocortical circuitry shows that visually induced LTP changes laminar connectivity in human visual cortex

Neuroplasticity is essential to learning and memory in the brain; it has therefore also been implicated in numerous neurological and psychiatric disorders, making measuring the state of neuroplasticity of foremost importance to clinical neuroscience. Long-term potentiation (LTP) is a key mechanism of neuroplasticity and has been studied extensively, and invasively in non-human animals. Translation to human application largely relies on the validation of non-invasive measures of LTP. The current study presents a generative thalamocortical computational model of visual cortex for investigating and replicating interlaminar connectivity changes using non-invasive EEG recording of humans. The model is combined with a commonly used visual sensory LTP paradigm and fit to the empirical EEG data using dynamic causal modelling. The thalamocortical model demonstrated remarkable accuracy recapitulating post-tetanus changes seen in invasive research, including increased excitatory connectivity from thalamus to layer IV and from layer IV to II/III, established major sites of LTP in visual cortex. These findings provide justification for the implementation of the presented thalamocortical model for ERP research, including to provide increased detail on the nature of changes that underlie LTP induced in visual cortex. Future applications include translating rodent findings to non-invasive research in humans concerning deficits to LTP that may underlie neurological and psychiatric disease.
A neuro‐based approach to designing a Wilkinson power divider

In this paper, a new neuro‐based approach using a feed‐forward neural network is presented to design a Wilkinson power divider. The proposed power divider is composed of symmetrical modified T‐shaped resonators, which are a replacement for quarter‐wave transmission lines in the conventional structure. The proposed technique reduces the size of the power divider by 45% and suppresses unwanted bands up to the fifth harmonics. To verify the concept, a prototype of the power divider has been fabricated and tested, exhibiting good agreement between the predicted and measured results. The results show that the insertion loss and the isolation at the center frequency are about 3.3 ± 0.1 dB and 23 dB, respectively.
Editorial for Special Issue “Energy Dissipation and Vibration Control: Materials, Modeling, Algorithm, and Devices”

Many engineering systems, from subsea pipelines to space structures, from moving vehicles to stationary skyscrapers, are subject to unwanted vibration excitations. Often vibration control can be considered as a problem of energy dissipation and vibration damping. The aims of this issue are to accumulate, disseminate, and promote new knowledge about vibration control, especially for topics related to energy dissipation methods for vibration damping. Topics in this issue reflect the start-of-the-arts in the field of vibration control, such as inerter dampers and pounding tuned mass dampers (PTMDs). This special issue also reports other types of new energy dissipation devices, including a multi-unit particle damper, a nonlinear eddy current damper, and layered dampers. Also reported in this issue are structural elements with innovative designs to dissipate energy. In addition, this special issue also reports two research studies on the dynamic responses of a structural foundation and an earth-retaining structure. Though most papers in this special issue are related to passive methods, one paper reports a semi-active vibration control via magnetorheological dampers (MRDs), and another two papers report active vibration controls using piezoelectric transducers and inertial actuators, respectively.
Predicting indirect effects of transportation network expansion on Asian elephants: Implications for environmental impact assessments

The rapid proliferation of transportation networks (TNs) threatens the viability of species with wide geographic ranges via habitat fragmentation, road kill, and indirect socio‐ecological interactions. Environmental impact assessments of TNs are mostly descriptive and focus on the direct impacts of the linear features of TNs, while the indirect and cumulative impacts are largely neglected. Using spatially explicit data of elephant‐caused damage from 2012 to 2015 in southwest China, we quantified the barrier effects of TNs on Asian elephant populations and predicted future patterns of damage under a TN expansion scenario using maximum entropy algorithms. The TNs acted as a strong barrier for the elephants, even in herds that have inhabited highly fragmented landscapes for years. Overall damage patterns were highly asymmetric around roads, with only 18% of events occurring on the far side of roads (relative to the core home range). Models predicted that TN expansion would reduce elephant habitats, exacerbating herd isolation and human–elephant conflict locally. Thus, we suggest that future environmental impact assessments should integrate mitigation of indirect conflicts.
Mitigating Risks Associated with Secondary Intravenous Infusions: An Empirical Evaluation of a Technology-based, Training-based, and Practice-based Intervention

Secondary infusions is a common method to deliver short infusions of intravenous (IV) drugs and fluids. Errors associated with this infusion method have led to patient safety concerns. This study's objective was to empirically evaluate interventions to mitigate secondary infusion risks. Three interventions, including a technology-based intervention (clamp detector on a smart pump), a training-based intervention (educational module), and a practice-based intervention (use of a separate pump for short infusions), were tested in a simulated inpatient unit. The technology-based intervention significantly decreased secondary clamp errors whereas the training-based intervention reduced complex pressure differential errors. The practice-based intervention was the only intervention that significantly decreased both secondary clamp errors and pressure differential errors, but introduced new risks due to mismanagement of residual volume in IV tubing. Study results highlight the need for a combination of mitigation strategies and can help guide the selection of interventions to reduce secondary infusion errors.
Genome Engineering Using the CRISPR Cas9 System

CRISPR technology is the most widely used genetic editing tool to edit, modify, delete, add and replace DNA sequences in both prokaryote and eukaryote, the normal CRISPR pathway cut gene at a specific point by recognizing a Protospacer Adjacent Motif (PAM) and induce double strand break, the cell can repair this destruction through Non- Homologous Enjoining. Scientist takes advantage of this break and inserts a homologous strand with specific changes through Homologous Directed Repair (HDR). CRISPR Interference (CRISPRi) follow the same technique but use a dead, mutated or inactive form Cas9 protein to render gene inactive and thereby block gene expression. In this study we compare both the similarities between CRISPR-Cas9 system and CRISPR Interference and further shown the differences of off-target in both systems.
Performance optimisation of cooperative spectrum sensing in mobile cognitive radio networks

Cooperative spectrum sensing is a key technology of cognitive radio networks (CRNs) to the reliability of spectrum sensing but is prone to be affected by a series of user characteristics, which results in a serious decline in the throughput of CRNs and the harmful interference to the primary user network. The performance analysis and optimisation of existing cooperative spectrum-sensing schemes do not completely cover key user characteristics. In this study, the joint effects of key user characteristics are studied with the objective to determine the parameters that affect the cooperative spectrum-sensing functionality. To this aim, the mobile CRN model and spatial–temporal spectrum-sensing model are formulated. Furthermore, the authors propose a dynamic double threshold energy detection (DDTED) scheme to derive the miss-detection probability and false alarm probability involving user characteristics. Moreover, the performance optimisation is carried out by a dynamic threshold factor. Finally, simulation results show that a variety of user characteristics have different effects on the performance of cooperative spectrum sensing, and the proposed DDTED scheme can achieve better performance than the existing approach.