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The recognition of named entities in the field of water conservancy is of great significance for the building of water conservancy knowledge graphs and intelligent question answering systems. However, in the current field of water conservancy, there are shortcomings in named entity recognition, such as a lack of annotated corpus, low recognition accuracy of traditional methods and inability to solve polysemous entities. Aiming at the characteristics of water conservancy texts, a Named Entity Recognition Model for Machine Reading Comprehension (MRC) based on data (vocabulary and entity type labels) enhancement, namely the MRC-WLE model was put forward. Mainly, the vocabulary feature information and entity type label feature information in water conservancy texts were injected into the model as "knowledge". It introduced models such as BERT-CRF, BERT-CRF-Word, BERT-BILSTM-CRF and BERT-BILSTM-CRF-Word as controls to evaluate the performance of the MRC-WLE model. The results show that compared with the BERT-CRF and other models mentioned above, the micro average F1 value of the MRC-WLE model has been improved. Compared with the MRC model, the micro average F1 value of the MRC-WLE model has been increased by 0.85%, reflecting the effectiveness of data augmentation. [ABSTRACT FROM AUTHOR]

Utilizing deep learning for data mining in biomedicine often falls short in leveraging prior knowledge and adapting to the complexities of biomedical literature mining. Entity recognition, a fundamental task in information extraction, also provides data support for Natural Language Processing (NLP) downstream tasks. Bovine Viral Diarrhea Virus (BVDV) results in considerable economic losses in the cattle industry due to calf diarrhea, bovine respiratory syndrome, and cow abortion. This study aims to extract information on BVDV from relevant literature and build a knowledge base. It enhances feature extraction in the BioBERT pre-trained model using the Machine Reading Comprehension (MRC) framework for information fusion and bi-directionally extracts corpus information through the Bi-LSTM network, followed by a CRF layer for decoding and prediction. The results show the construction of a BVDV Corpus with 22 biomedical entities and introduce the BioBERT-Bi-LSTM-CRF Integrated with MRC (BBCM) model for Named Entity Recognition (NER), combining prior knowledge and the reading comprehension framework (MRC). The BBCM model achieves F 1 -scores of 78.79% and 76.3% on the public datasets JNLPBA and GENIA, respectively, and 67.52% on the BVDV Corpus, outperforming other models. This research presents a targeted NER method for BVDV, effectively identifying related entities and exploring their relationships, thus providing valuable data support for NLP's downstream tasks. [ABSTRACT FROM AUTHOR]

Recently, cell-free (CF) architectures, in which every user can potentially communicate with every base station, have received a lot of attention. This paper considers the uplink of fully and partially centralized CF networks where unmanned aerial vehicles serve as flying base stations (FBSs). A subset of FBSs participates in the reception of each user and a subset of users is received by each FBS. Deterministic equivalent expressions, exact asymptotically in the subset sizes and approximate for finite dimensions thereof, are derived for the spectral efficiency under Rician fading. Capitalizing on these expressions, the FBS deployment problem is investigated for different receiver architectures. The nonconvex deployment problem, tackled through a combination of gradient-based and Gibbs sampling algorithms, results in a superior performance with respect to a square grid deployment; this superiority extends to the minimum and aggregate spectral efficiency for both fully and partially centralized cell-free networks.

To better combat the devastation of the protected forests in Côte d'Ivoire, a study was conducted to create a technique for detecting the acoustic signals produced by chainsaws deployed to fell trees in these areas. To improve the recognition rate of chainsaw sounds in a forest environment and increase the detection range of the recognition system, we are implementing the maximum ratio combining (MRC) technique on a microphone array. Therefore, the employment of an identification system is compared using one (01) microphone against the outcomes obtained by adopting system with three (03), six (06), and twelve (12) microphones. The use of MRC is then contrasted with an alternative recombining approach, designated as simple summation (SS). The SS is characterised by the simple addition of the signals acquired by the microphone array in the frequency domain. The MRC was employed on various microphone arrangements, accounting for varying degrees of attenuation experienced by chainsaw sounds. The K-Nearest Neighbors, in combination with Mel Frequency Cepstral Coefficients (MFCC), was employed to detect chainsaw sounds within the 16 kHz central frequency octave band. MRC applied to microphone arrays provided superior outcomes than simple summation. The enhancement in terms of classification rate ranged from [18; 51], favouring MRC. Moreover, it extended the chainsaw detection range from 520 m (using one microphone) to 1210 m (using a 12-microphone array). Taking into account the criteria for selecting an optimum microphone array, including classification rate, number of microphone nodes, information processing time and detection range, the six-microphone array was chosen as the best configuration. This configuration boasts a theoretical detection range of 1040 meters. [ABSTRACT FROM AUTHOR]

Machine Reading Comprehension (MRC) is a task that enables machines to mirror key cognitive processes involving reading, comprehending a text passage, and answering questions about it. There has been significant progress in this task for English in recent years, where recent systems not only surpassed human-level performance but also demonstrated advancements in emulating complex human cognitive processes. However, the development of Arabic MRC has not kept pace due to language challenges and the lack of large-scale, high-quality datasets. Existing datasets are either small, low quality or released as a part of large multilingual corpora. We present the Arabic Question Answering Dataset (ArQuaD), a large MRC dataset for the Arabic language. The dataset comprises 16,020 questions posed by language experts on passages extracted from Arabic Wikipedia articles, where the answer to each question is a text segment from the corresponding reading passage. Besides providing various dataset analyses, we fine-tuned several pre-trained language models to obtain benchmark results. Among the compared methods, AraBERTv0.2-large achieved the best performance with an exact match of 68.95% and an F1-score of 87.15%. However, the significantly higher performance observed in human evaluations (exact match of 86% and F1-score of 95.5%) suggests a significant margin of possible improvement in future research. We release the dataset publicly at https://github.com/RashaMObeidat/ArQuAD to encourage further development of language-aware MRC models for the Arabic language. [ABSTRACT FROM AUTHOR]

The deployment of cooperative communication inside a cell-Free mMIMO system can improve both the spectral efficiency SE performance as well as the energy efficiency EE performance. This increase is due to the increase in the signal to interference plus noise ratio SINR. In fact, the SINR can be greatly improved when the cognitive radio theory is applied due to its capability of interference mitigation. In this manuscript, the cognitive intelligent reflecting surfaces IRSs are distributed inside a cell-Free mMIMO system in order to improve the SE as well as the EE performance. Moreover, the cognitive radio can raise each user SINR. In this manuscript, the authors try to carry out the suitable mathematical model for the fore-mentioned system. Moreover, the system will be simulated. Subsequently, the simulation results will be explained. It is obvious that the implantation of cognitive IRSs inside, cell-Free mMIMO systems can greatly increase the system performance. [ABSTRACT FROM AUTHOR]

Machine reading comprehension is introduced to improve machines' readability and understandability of human languages. This sophisticated version of natural language processing is used for testing and improving the machine's efficiency for reading and responding to the input texts for appropriate queries. In this article, a persistent comprehensive model using query reconstruction is introduced to address the "Cloze Style" issue in text reading. This issue results in multiple output delivery that serves as irrelevant for different input queries. Therefore, the query reconstruction using the possible combination, reducing the aforementioned issue, is introduced in this model. The possible query keywords are replaced using the maximum individual combinations. The combinations are swapped using deep learning through keyword training and substitution processes. This process is persistent until the maximum text output (answer/ response) is obtained from the machine. The output is used for analyzing the understandability of the machine based on which the training intensity is tuned for successive iterations. Therefore, the proposed model scrutinizes output accuracy by reducing errors under controlled combination time. [ABSTRACT FROM AUTHOR]

Implementation of an eRehabilitation intervention named Fit After Stroke @Home (Fast@home) – including cognitive/physical exercise applications, activity-tracking, psycho-education – after stroke resulted in health-related improvements. This study investigated what worked and why in the implementation. Implementation activities (information provision, integration of Fast@home, instruction and motivation) were performed for 14 months and evaluated, using the Medical Research Council framework for process evaluations which consists of three evaluation domains (implementation, mechanisms of impact and contextual factors). Implementation activities were evaluated by field notes/surveys/user data, it's mechanisms of impact by surveys and contextual factors by field notes/interviews among 11 professionals. Surveys were conducted among 51 professionals and 73 patients. User data (n = 165 patients) were extracted from the eRehabilitation applications. Implementation activities were executed as planned. Of the professionals trained to deliver the intervention (33 of 51), 25 (75.8%) delivered it. Of the 165 patients, 82 (49.7%) were registered for Fast@home, with 54 patient (65.8%) using it. Mechanisms of impact showed that professionals and patients were equally satisfied with implementation activities (median score 7.0 [IQR 6.0–7.75] versus 7.0 [6.0–7.5]), but patients were more satisfied with the intervention (8.0 [IQR 7.0–8.0] versus 5.5 [4.0–7.0]). Guidance by professionals was seen as most impactful for implementation by patients and support of clinical champions and time given for training by professionals. Professionals rated the integration of Fast@home as insufficient. Contextual factors (financial cutbacks and technical setbacks) hampered the implementation. Main improvements of the implementation of eRehabilitation are related to professionals' perceptions of the intervention, integration of eRehabilitation and contextual factors. To increase the use of eRehabilitation by patients, patients should be supported by their healthcare professional in their first time use and during the rehabilitation process. To increase the use of eRehabilitation by healthcare professionals, healthcare professionals should be (1) supported by a clinical champion and (2) provided with sufficient time for learning to work and getting familiar with the eRehabilitation program. Integration of eRehabilitation in conventional stroke rehabilitation (optimal blended care) is an important challenge and a prerequisite for the implementation of eRehabilitation in the clinical setting. [ABSTRACT FROM AUTHOR]

In an advanced wireless communication system, a smart receiver trims down the fading effect. From a practical point of view, performance such receiver depends not only on the estimation of channels but also system accuracy. This paper derives the general expression of average bit error rate (BER) and outage probability for dual-branch Maximum Ratio Combining (2-MRC) over Fluctuating Two Ray (FTR) fading channels with Imperfect Channel Estimation. Communication channels encountered in Fifth-Generation Millimeter-Wave communication is represented accurately by the FTR fading channels. A 2-MRC receiver is considered because of its performance advantage and less complexity. The probability density function of the output signal-to-noise ratio is obtained for 2-MRC receiver with channel estimation error over the FTR fading model. The mathematical description of average BER for both non-coherent and binary coherent modulation is derived. The impact of the fading parameters and the error estimation on the system efficiency are assessed through numerical analysis of the generated equations. [ABSTRACT FROM AUTHOR]

In order to meet the growing needs of the world economy for biotechnology, culture collections must transform the way they operate from passive storage of microbial resources to active microbial resource centers whose services should go beyond the provision of microbes. The protection and conscious use of microorganisms aims to co-create a strategy for responsible and sustainable development, based on expert knowledge. This article deals with the subject of the recently developed panel of biobank-specific standards and the requirements that must be met by culture collections to transform into modern microbial biobanks.

Towards the 5Gnetworks and beyond, there are a lot of emerging technologies. These technologies include but not limited to; multiple input multiple output (MIMO), cell-Free networks, and millimeter wave bands. The cellular MIMO can provide a satisfied performance for users except the shadowed and the cell-edge ones. In order to overcome this disadvantage, the cell-Free networks are deployed. Through applications of distributed access points (APs), the cell-Free networks can provide a ubiquitous coverage for users as whole. Therefore, they can provide a high throughput for users. Moreover, the applications of millimeter wave bands can provide a high bandwidth and hence, a high throughput for users. In other words, the application of the cell-Free technology combined with the millimeter wave bands can extremely enlarge the users' throughput. This is the motivation of our manuscript. The purpose of this manuscript is to provide mathematical model and simulation for the cell-Free mMIMO network, operating in the millimeter wave bands. The performance metrics can include; the spectral efficiency (SE), bit error rate (BER), and energy efficiency (EE). It is observed that the centralized cooperation among the APs can let users have a satisfied throughput even the system employs the maximal ratio combining (MRC). Furthermore, all cooperation levels, among APs, can perform well even for non-light of sight (NLOS) environment. [ABSTRACT FROM AUTHOR]

The implementation of massive multiple input multiple output systems mMIMO can greatly enhance the spectral efficiency SE performance for users. Although, the cell-edge users as well as indoor users still have a bad performance. The cell-Free network, wherein the large number of existing antennas is replaced by the same number of distributed access points APs, can enlarge the SE performance even for shadowed users. The performance can be further enhanced after application of cooperation. When a Cell-Free mMIMO system is enriched with intelligent reflecting surfaces IRS, its performance may be improved. In this manuscript, the authors will carry out the mathematical model and simulation for the Cell-Free networks employing IRSs. The performance metrics can include the SE as well as energy efficiency EE. From the simulation results, it can be observed that implementation of IRSs inside the cell-Free networks can greatly increase the SE and EE of the system. [ABSTRACT FROM AUTHOR]

Passive radar is an interesting approach in the context of non-cooperative target detection. Because the signal source takes advantage of the so-called illuminator of opportunity (IoO), the deployed system is silent, allowing the operator cheap, portable, and practically undetectable deployments. These systems match perfectly with the use of antenna arrays to take advantage of the additional gains provided by the coherent combination of the signals received at each element. To obtain these benefits, linear processing methods are required to enhance the system's performance. In this work, we summarize the main beamforming methods in the literature to provide a clear picture of the current state of the art. Next, we perform an analysis of the benefits and drawbacks and explore the chance of increasing the number of antenna elements. Finally, we identify the major challenges to be addressed by researchers in the future. [ABSTRACT FROM AUTHOR]

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In the remote sensing monitoring of conservation tillage, the acquisition of remote sensing data with high spatial and temporal resolution is critical. The current optical remote sensing images cannot realize both temporal and spatial resolution, especially under cloud and rain interference. Thus, this study employs the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) to obtain the normalized difference tillage index (NDTI) with both temporal and spatial resolution estimated by Sentinel−2 and MODIS using the Index−then−Blend (IB) and Blend−then−Index (BI) fusion schemes. After comparison, the IB scheme was better than the BI scheme in predicting results and prediction efficiency. The NDTI predicted by ESTARFM and Sentinel−2 on June 12, 2020 was compared. A coefficient of determination R2 of 0.73 and RMSE of 0.000117 was obtained, indicating a high prediction accuracy, which meets the prediction requirements. Based on the predicted ESTARFM NDTI of the study area on May 17, 2021, the maize residue cover (MRC) of the study area was estimated using the previously constructed MRC unary linear regression model. The MRC of the sampling points of the remote sensing images was estimated by verifying the predicted ESTARFM NDTI with the MRC of the sampling points taken in the field extracted by the maximum likelihood classifier, which has a coefficient of determination R2 of 0.78 and RMSE of 0.00676, signifying better prediction results. The proposed method provides considerable data sources for the remote sensing monitoring studies of conservation tillage. [ABSTRACT FROM AUTHOR]

Background: chronic idiopathic demyelinating polyneuropathy (CIDP) is an acquired, immune-mediated neuropathy characterized by weakness, sensory symptoms and significant reduction or loss of deep tendon reflexes evolving over 2 months at least, associated with electrophysiological evidence of peripheral nerve demyelination. Recently, subcutaneous immunoglobulins (SCIg) have been introduced in clinical practice as a maintenance therapy for CIDP; nevertheless, electrophysiological and efficacy data are limited. Methods: to evaluate SCIg treatment efficacy, we retrospectively reviewed data from 15 CIDP patients referring to our clinic, receiving SCIg treatment and who performed electrophysiological studies (NCS) and clinical scores (MRC sumscore, INCAT disability score and ISS) before starting the treatment and at least one year after. Results: NCS showed no significant changes before and during treatment for all the nerves explored. Clinical scores did not significantly change between evaluations. Correlation analysis evidenced a positive correlation of cMAPs distal amplitude with MRC sumscore and a trend of negative correlation with the INCAT disability score. Conclusions: SCIg maintenance therapy preserves nerve function in CIDP with a good efficacy and safety. Treatment effectiveness can be assessed with ENG, which represents a useful instrument in the follow-up and prognostic assessment of CIDP. [ABSTRACT FROM AUTHOR]

Background: Hand tendon reconstruction is required in both acute and chronic tendon injuries. A number of donor sites have been described; one such novel donor site is semitendinosus tendon used a graft for hand tendon reconstruction. Based on data reviewed, only a few cases are described up till now. Objective: Utility of semitendinosus tendon graft with adequacy of tendon material for hand tendon reconstruction and minimal donor site morbidity Methods: Semitendinosus tendon was utilized in total of 18 patients undergoing tendon reconstruction for chronic tendon injuries and for tendon transfer to achieve adequate length. All cases were performed during January 2019 To December 2020. Full length uni/bilateral semi-tendinosus tendon was harvested using a tendon harvester. Tendon was used as a single slip or was split into further slips as needed for tendon reconstruction. Post operatively splints were continued as per protocol (keeping splint for 6 weeks, encouraging active physiotherapy at 8 weeks, continuing night splintage for total of 10 weeks and advising patient to avoid lifting heavy weight for at least 12 weeks). Patients were followed with assessment of strength via MRC (Medical Research Council) grading scale, and tendon excursion measurements via tip to palm distance. Results: Patients had a mean age for 27.5±2.3 with a predominant male population (72.2%). Post-operative assessment showed finger strength of MRC 5 in twelve patients and MRC 4 in three and MRC 3 in three patients. Tendon excursion was documented measuring a tip to palm distance. Three patients developed tendon adhesions which were treated with tenolysis. Conclusion: Semitendinosus is a recommended option for hand tendon (both flexor & extensor) reconstruction, providing adequate length & strength for reconstruction with high predictable availability and reliability. Although Palmaris longus remains the recommended option for single tendon reconstruction, it is absent in a few cases or is rudimentary, making it difficult to be utilized. [ABSTRACT FROM AUTHOR]

The cell-Free massive multiple input multiple output "mMIMO" networks can provide a satisfied performance for the fifth generation "5G" systems and beyond even there are shadowed users or indoor ones. The performance of the cell-Free mMIMO systems was mathematically analyzed and simulated in a lot of previous works. However, this work aims to provide a complete mathematical model and simulation for a cell-Free mMIMO system that applies relays which operate with the cognitive radio theory. The proposed work can provide novel contributions on two axes. Firstly, the relays can improve the coverage performance of a cell-Free mMIMO network especially at shadowed users, indoor users, and the cell-edge ones. Secondly, the cognitive radio can mitigate the interference in a cell-Free mMIMO network. The interference mitigation results in performance enhancement. Therefore, the cell-Free mMIMO network, based on cognitive relays, is studied. The proposed system is mathematically analyzed and simulated. The spectral efficiency "SE" and signal to interference plus noise ratio "SINR" is deduced. They are given in a closed form formula. It can be concluded that the cognitive relays can improve; SINR, SE, and Energy Efficiency "EE" of a cell-Free mMIMO system. [ABSTRACT FROM AUTHOR]

We experimentally demonstrate the transmission of 20-Gbaud QPSK millimeter-wave signals within a 1.2-km wireless range at 128-GHz using constant-modulus-algorithm (CMA) and the maximum ratio combining (MRC) technology with over 2.2-dB gain in a photonics-assisted millimeter wave (MMW) 1 × 2 Single Input Multi Output (SIMO) communication system. MRC is applied for SIMO signal merging which leads to Signal to Noise Ratio (SNR) enhancement and significant Bit Error Rate (BER) reduction. The comparison which is performed for Single Input Single Output (SISO) and SIMO system, demonstrates the BER improvement. To the best of our knowledge, this is the first experimental demonstration of high gain in a D-band MMW 1 × 2 SIMO system by using these technologies. [ABSTRACT FROM AUTHOR]

A stack distance of a reference is the depth from which the reference must be extracted from a stack. It has been widely applied to a variety of applications utilizing temporal locality information. However, calculating an exact stack distance requires significant computational complexity that is impractical for online production systems. This paper proposes an efficient algorithm that approximates a stack distance based on workload characteristics. The proposed algorithm utilizes two simple reference metrics: inter-reference distance and a quasi-unique reference count. More importantly, its approximation algorithm requires surprisingly simple calculation. Consequently, it significantly reduces computational overhead while exhibiting exceptional accuracy and runs extremely fast. Moreover, it allows configurable parameters for performance optimization by making optimal use of workload characteristics. Our extensive experiments with diverse realistic workloads demonstrate our stack distance approximation algorithm outperforms the current state-of-the-art algorithm with higher accuracy ( $3.7\times $ ), lower memory footprint ( $3.05\times $ ) and fast execution (less than 0.05 seconds) on average. In addition, with configuration parameters, our refined algorithm can achieve a 28% average additional accuracy improvement.

Intervention development frameworks offer the behavioral sciences a systematic and rigorous empirical process to guide the translation of basic science into practice in pursuit of desirable public health and clinical outcomes. The multiple frameworks that have emerged share a goal of optimization during intervention development and can increase the likelihood of arriving at an effective and disseminable intervention. Yet, the process of optimizing an intervention differs functionally and conceptually across frameworks, creating confusion and conflicting guidance on when and how to optimize. This paper seeks to facilitate the use of translational intervention development frameworks by providing a blueprint for selecting and using a framework by considering the process of optimization as conceptualized by each. First, we operationalize optimization and contextualize its role in intervention development. Next, we provide brief overviews of three translational intervention development frameworks (ORBIT, MRC, and MOST), identifying areas of overlap and divergence thereby aligning core concepts across the frameworks to improve translation. We offer considerations and concrete use cases for investigators seeking to identify and use a framework in their intervention development research. We push forward an agenda of a norm to use and specify frameworks in behavioral science to support a more rapid translational pipeline.

Olga Kennard (née Weisz, 1924–2023) was a true pioneer in crystallography. She left a lasting mark on scientific research with the establishment of the Cambridge Crystallographic Data Centre (CCDC). [ABSTRACT FROM AUTHOR]

In this study, the authors provide a direct comparison made between whole tree-harvesting (WTH) and cut-to length (CTL) methods, which was conducted in two sites in the Slovak Republic and applied to poplar plantations. Both systems, WTH and CTL, have been employed at the highest mechanization level in two sites: "Nivky" and "Skalica". Two different strategies, namely, "mass handling" and "small-scale mechanization", have been used for WTH and CTL, respectively. The study results showed that the level of productivity (ODT SMH−1) in the felling operation was almost double for WTH than for the CTL method in Nivky (+84%) and more than double in Skalica (+113%). The extraction operation under WTH showed a productivity increase from one fifth (+20%) to more than double (104%) that of the CTL method in the Nivky and Skalica sites, respectively. Regarding cost-efficiency (EUR ODT−1), the WTH system offers a similar trend except with respect to extraction in Nivky (higher productivity site), in which the CTL extraction was 4.5% less expensive than the WTH extraction. The study results show that the mass-handling technique deployed in the WTH system offers very good performance in poorer plantations since the very small tree size and low-growing stock challenge the CTL system more than the WTH system. The total operation (felling, bucking, and extraction) costs (EUR ODT−1) recorded by the study in commercial conditions (as contractors perform for revenue purposes) were 32.50 and 45.80 EUR ODT−1 for CTL and 43.30 and 53.60 EUR ODT−1 for WTH for the higher-yield site (Nivky) and lower-yield site (Skalica), respectively. Regarding the WTH System, the researchers found that the drop in efficiency (and the consequent rise in the costs-per-ton of product) depends largely on the bucking phase conducted using the harvester at the landing of the stacked piles of interlocked trees. The main results of this study demonstrate the promising strategy of mass handling associated with the WTH system in medium rotation coppice (MRC) harvesting and shows that bucking is the weaker phase. Future efforts must be made to ensure feasibility of the "mass handling" strategy alongside the entire workflow by means of finding suitable mobile machinery that can delimb, debark, and crosscut tree bunches instead of single trees. [ABSTRACT FROM AUTHOR]

Mulberry (Morus species) leaves are the sole source of food for the silkworm (Bombyx mori L.) hence, high-quality foliage is the key to the productivity of the silk industry. Rapid water loss from the harvested leaves is one of the major reasons for quality loss affecting silkworm feeding behaviour. Previous research in our laboratory indicated that epicuticular wax is essential in maintaining leaf moisture in harvested leaves of mulberry. In the present study, an agronomic approach was designed and tested to increase the cuticular resistance and enhance moisture retention capacity in the harvested leaves in two genotypes of mulberry, Dudia white (DW) and Matigara white (MW). Controlled irrigation and mild drought stress increased leaf epicuticular wax and drought-stressed plants had a significantly higher wax load (465.31 and 556.29 μg dm-2 in Dudia white and Matigara white, respectively) at 40 per cent soil field capacity (FC) when compared to the plants grown at 100 per cent FC. The harvested leaves showed higher moisture retention capacity (MRC) of 92 and 84.74 per cent at 40 per cent FC compared to 62.55 and 57.10 per cent at 100 per cent FC in Dudia white and Matigara white, respectively. Leaves from water-limited plants had significantly lower water loss of 3.4 and 5.9 per cent under 40 per cent FC compared to control plants (6.6 and 9.1%). The technique used in this study increased MRC and helped in preserving leaf quality. The approach developed is cost-effective and can be easily adopted in farmer’s fields. [ABSTRACT FROM AUTHOR]

In this paper, we have formulated a novel expression of the probability density function (PDF) of the L-MRC receiver over correlated η − μ channel considering the existing error in the estimation of the channel coefficients. The derived PDF is used to calculate the average bit error rate of the Quadrature Amplitude Modulation (QAM) scheme and further performance analysis of the receiver has been done with respect to this modulation. The performance of the receiver in terms of different channel and receiver performance parameters has been plotted and discussed in the results section. The results are verified with the help of the Monte Carlo simulation. [ABSTRACT FROM AUTHOR]

Passive radar is an interesting approach in the context of non-cooperative target detection. Because the signal source takes advantage of the so-called illuminator of opportunity (IoO), the deployed system is silent, allowing the operator cheap, portable, and practically undetectable deployments. These systems match perfectly with the use of antenna arrays to take advantage of the additional gains provided by the coherent combination of the signals received at each element. To obtain these benefits, linear processing methods are required to enhance the system’s performance. In this work, we summarize the main beamforming methods in the literature to provide a clear picture of the current state of the art. Next, we perform an analysis of the benefits and drawbacks and explore the chance of increasing the number of antenna elements. Finally, we identify the major challenges to be addressed by researchers in the future.

This paper develops three low-complexity detection schemes for the spatial modulation (SM) Multiple Input Multiple Output (MIMO) systems. We first propose a reduced complexity maximum likelihood (RC-ML) detection scheme. For the practical values of the modulation index, the proposed RC-ML method is simpler than the existing hard-limiting-based ML schemes. The two other proposals are based on a suboptimal Maximum Ratio Combining (MRC) detection method. We present a new analysis of the MRC detector in the uncorrelated Rayleigh fading channel and identify the system operational scenarios for which the MRC performance is nearly identical to the ML performance. Our proposals — a hybrid MRC-ML method and an MRC scheme with rank reduction — are inspired by this analysis. The analytical and simulation results show that the proposed MRC-based schemes can attain a near-optimal performance while reducing the complexity of the ML-based SM receiver. [ABSTRACT FROM AUTHOR]

Cellular networks have been evolving at a great pace recently to keep up with the rapidly increasing demand for wireless data services. To cater for this demand, advanced technologies will be implemented in the next generation of cellular network. A promising technology, known as Massive Multiple-Input Multiple-Output (MIMO), will satisfy the high data rate requirement of wireless services. The concept of massive MIMO is based on installing hundreds or thousands of antenna elements at the BS and only one antenna at the user terminal. The beneficial effect of employing such large antenna elements is that unprecedented antenna gains and a spatial resolution that allows multi-user massive MIMO communication to a large number of users per cell can be obtained while maintaining robustness to inter-user interferences. The problem of finding theoretical sum-rate and efficiency under imperfect CSI (Channel State Information) for each mobile user that matches closely to realistic 5G models reduces to the application of these theoretical analysis to practical 5G spatial model with both the Line-Of-Sight and Non-LOS propagation paths. To this end, we propose a solution to this problem by applying an uplink theoretical analysis of a Multi-User massive MIMO system under imperfect CSI, with multiple cells, to the 5G spatial channel model. Also, we formulate an optimization problem for our analysis and maximize the spectral efficiency per unit cell of the massive MIMO system. In this paper, two commonly used linear receivers namely the Maximum Ratio Combining and Zero-Forcing (ZF) are considered. The Signal and Noise Interference Ratio analysis for our proposed Multi-User massive MIMO system is described and closed-form expressions are derived for the sum-rate, spectral and energy efficiencies for each mobile user with random displacement in the multi-cell network. Our analysis takes into account the effect of inter-cell interference. It is shown through simulations that with only 200 BS antennas a Zero Forcing (ZF) receiver, under maximum inter-cell interference, can attain an uplink spectral efficiency of around 76 bps/Hz/cell for the 5G spatial channel whilst for the uncorrelated Rayleigh channel case this figure drops drastically to around 20 bps/Hz/cell. [ABSTRACT FROM AUTHOR]