Craniocerebral injuries in war against terrorism --- A contemporary series from Pakistan

Objective: Terrorism-related bomb attacks on civilian population have increased dramatically over the last decade. Craniocerebral injuries secondary to improvised explosive devices have not been widely reported in the context of unarmored civilians. This series intends to report the spectrum of these injuries secondary to suicidal and implanted bombs as encountered at the Aga Khan University Hospital, Pakistan (AKUH). Further, a few pertinent management guidelines have also been discussed.Methods: The hospital database and clinical coding during a 5-year period were examined for head injuries secondary to terrorism-associated blasts. In addition to patient demographics, data analysis for our series included initial Glasgow Coma Scale, presenting neurological complaints, associated non-neurological injuries, management (conservative or operative) to associated complications, and discharge neurological status.Results: A total of 16 patients were included in this series. Among them 9 were victims of suicidal blasts while 7 were exposed to implanted devices. The patients presented with diverse patterns of injury secondary to a variety of shrapnel. A follow-up record was available for 12 of the 16 patients (mean follow-up: 7.8 months), with most patients having no active complaints.Conclusion: The results of this series show that civilian victims of suicidal and improvised bombings present with a wide range of neurological symptoms and injury patterns, which often differ from the neurological injuries incurred by military personnel in similar situations, and thereby often require individualized care

Optimized Cluster-Based Dynamic Energy-Aware Routing Protocol for Wireless Sensor Networks in Agriculture Precision

[EN] Wireless sensor networks (WSNs) are becoming one of the demanding platforms, where sensor nodes are sensing and monitoring the physical or environmental conditions and transmit the data to the base station via multihop routing. Agriculture sector also adopted these networks to promote innovations for environmental friendly farming methods, lower the management cost, and achieve scientific cultivation. Due to limited capabilities, the sensor nodes have suffered with energy issues and complex routing processes and lead to data transmission failure and delay in the sensor-based agriculture fields. Due to these limitations, the sensor nodes near the base station are always relaying on it and cause extra burden on base station or going into useless state. To address these issues, this study proposes a Gateway Clustering Energy-Efficient Centroid- (GCEEC-) based routing protocol where cluster head is selected from the centroid position and gateway nodes are selected from each cluster. Gateway node reduces the data load from cluster head nodes and forwards the data towards the base station. Simulation has performed to evaluate the proposed protocol with state-of-the-art protocols. The experimental results indicated the better performance of proposed protocol and provide more feasible WSN-based monitoring for temperature, humidity, and illumination in agriculture sector.This work has also been partially supported by the European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities and beyond) project ERANETMED3-227 SMARTWATIR.Qureshi, KN.; Bashir, MU.; Lloret, J.; León Fernández, A. (2020). Optimized Cluster-Based Dynamic Energy-Aware Routing Protocol for Wireless Sensor Networks in Agriculture Precision. Journal of Sensors. 2020:1-19. https://doi.org/10.1155/2020/9040395S1192020Sneha, K., Kamath, R., Balachandra, M., & Prabhu, S. (2019). New Gossiping Protocol for Routing Data in Sensor Networks for Precision Agriculture. Soft Computing and Signal Processing, 139-152. doi:10.1007/978-981-13-3393-4_15Qureshi, K. N., Abdullah, A. H., Bashir, F., Iqbal, S., & Awan, K. M. (2018). Cluster-based data dissemination, cluster head formation under sparse, and dense traffic conditions for vehicular ad hoc networks. International Journal of Communication Systems, 31(8), e3533. doi:10.1002/dac.3533Rault, T., Bouabdallah, A., & Challal, Y. (2014). Energy efficiency in wireless sensor networks: A top-down survey. Computer Networks, 67, 104-122. doi:10.1016/j.comnet.2014.03.027Feng, X., Zhang, J., Ren, C., & Guan, T. (2018). An Unequal Clustering Algorithm Concerned With Time-Delay for Internet of Things. IEEE Access, 6, 33895-33909. doi:10.1109/access.2018.2847036Savaglio, C., Pace, P., Aloi, G., Liotta, A., & Fortino, G. (2019). Lightweight Reinforcement Learning for Energy Efficient Communications in Wireless Sensor Networks. IEEE Access, 7, 29355-29364. doi:10.1109/access.2019.2902371Srbinovska, M., Gavrovski, C., Dimcev, V., Krkoleva, A., & Borozan, V. (2015). Environmental parameters monitoring in precision agriculture using wireless sensor networks. Journal of Cleaner Production, 88, 297-307. doi:10.1016/j.jclepro.2014.04.036Lloret, J., Garcia, M., Bri, D., & Diaz, J. (2009). A Cluster-Based Architecture to Structure the Topology of Parallel Wireless Sensor Networks. Sensors, 9(12), 10513-10544. doi:10.3390/s91210513Qureshi, K. N., Din, S., Jeon, G., & Piccialli, F. (2020). Link quality and energy utilization based preferable next hop selection routing for wireless body area networks. Computer Communications, 149, 382-392. doi:10.1016/j.comcom.2019.10.030Kumar, S. A., & Ilango, P. (2017). The Impact of Wireless Sensor Network in the Field of Precision Agriculture: A Review. Wireless Personal Communications, 98(1), 685-698. doi:10.1007/s11277-017-4890-zAnisi, M. H., Abdul-Salaam, G., & Abdullah, A. H. (2014). A survey of wireless sensor network approaches and their energy consumption for monitoring farm fields in precision agriculture. Precision Agriculture, 16(2), 216-238. doi:10.1007/s11119-014-9371-8Long, D. S., & McCallum, J. D. (2015). On-combine, multi-sensor data collection for post-harvest assessment of environmental stress in wheat. Precision Agriculture, 16(5), 492-504. doi:10.1007/s11119-015-9391-zFu, X., Fortino, G., Li, W., Pace, P., & Yang, Y. (2019). WSNs-assisted opportunistic network for low-latency message forwarding in sparse settings. Future Generation Computer Systems, 91, 223-237. doi:10.1016/j.future.2018.08.031Mehmood, A., Khan, S., Shams, B., & Lloret, J. (2013). Energy-efficient multi-level and distance-aware clustering mechanism for WSNs. International Journal of Communication Systems, 28(5), 972-989. doi:10.1002/dac.2720Pantazis, N. A., Nikolidakis, S. A., & Vergados, D. D. (2013). Energy-Efficient Routing Protocols in Wireless Sensor Networks: A Survey. IEEE Communications Surveys & Tutorials, 15(2), 551-591. doi:10.1109/surv.2012.062612.00084De Farias, C. M., Pirmez, L., Fortino, G., & Guerrieri, A. (2019). A multi-sensor data fusion technique using data correlations among multiple applications. Future Generation Computer Systems, 92, 109-118. doi:10.1016/j.future.2018.09.034Rao, P. C. S., Jana, P. K., & Banka, H. (2016). A particle swarm optimization based energy efficient cluster head selection algorithm for wireless sensor networks. Wireless Networks, 23(7), 2005-2020. doi:10.1007/s11276-016-1270-7Fu, X., Fortino, G., Pace, P., Aloi, G., & Li, W. (2020). Environment-fusion multipath routing protocol for wireless sensor networks. Information Fusion, 53, 4-19. doi:10.1016/j.inffus.2019.06.001Liu, X. (2015). Atypical Hierarchical Routing Protocols for Wireless Sensor Networks: A Review. IEEE Sensors Journal, 15(10), 5372-5383. doi:10.1109/jsen.2015.2445796Jan, N., Javaid, N., Javaid, Q., Alrajeh, N., Alam, M., Khan, Z. A., & Niaz, I. A. (2017). A Balanced Energy-Consuming and Hole-Alleviating Algorithm for Wireless Sensor Networks. IEEE Access, 5, 6134-6150. doi:10.1109/access.2017.2676004Gupta, G. P., Misra, M., & Garg, K. (2014). Energy and trust aware mobile agent migration protocol for data aggregation in wireless sensor networks. Journal of Network and Computer Applications, 41, 300-311. doi:10.1016/j.jnca.2014.01.003Safa, H., Karam, M., & Moussa, B. (2014). PHAODV: Power aware heterogeneous routing protocol for MANETs. Journal of Network and Computer Applications, 46, 60-71. doi:10.1016/j.jnca.2014.07.035Liu, X. (2015). An Optimal-Distance-Based Transmission Strategy for Lifetime Maximization of Wireless Sensor Networks. IEEE Sensors Journal, 15(6), 3484-3491. doi:10.1109/jsen.2014.2372340Brar, G. S., Rani, S., Chopra, V., Malhotra, R., Song, H., & Ahmed, S. H. (2016). Energy Efficient Direction-Based PDORP Routing Protocol for WSN. IEEE Access, 4, 3182-3194. doi:10.1109/access.2016.2576475Abo-Zahhad, M., Ahmed, S. M., Sabor, N., & Sasaki, S. (2015). Mobile Sink-Based Adaptive Immune Energy-Efficient Clustering Protocol for Improving the Lifetime and Stability Period of Wireless Sensor Networks. IEEE Sensors Journal, 15(8), 4576-4586. doi:10.1109/jsen.2015.2424296Huynh, T.-T., Dinh-Duc, A.-V., & Tran, C.-H. (2016). Delay-constrained energy-efficient cluster-based multi-hop routing in wireless sensor networks. Journal of Communications and Networks, 18(4), 580-588. doi:10.1109/jcn.2016.000081Shen, J., Wang, A., Wang, C., Hung, P. C. K., & Lai, C.-F. (2017). An Efficient Centroid-Based Routing Protocol for Energy Management in WSN-Assisted IoT. IEEE Access, 5, 18469-18479. doi:10.1109/access.2017.2749606Awan, K. M., Shah, P. A., Iqbal, K., Gillani, S., Ahmad, W., & Nam, Y. (2019). Underwater Wireless Sensor Networks: A Review of Recent Issues and Challenges. Wireless Communications and Mobile Computing, 2019, 1-20. doi:10.1155/2019/6470359Sajwan, M., Gosain, D., & Sharma, A. K. (2018). CAMP: cluster aided multi-path routing protocol for wireless sensor networks. Wireless Networks, 25(5), 2603-2620. doi:10.1007/s11276-018-1689-0Varga, A. (2010). OMNeT++. Modeling and Tools for Network Simulation, 35-59. doi:10.1007/978-3-642-12331-3_3Lartillot, O., Toiviainen, P., & Eerola, T. (2008). A Matlab Toolbox for Music Information Retrieval. Studies in Classification, Data Analysis, and Knowledge Organization, 261-268. doi:10.1007/978-3-540-78246-9_31Mathur, P., Nielsen, R. H., Prasad, N. R., & Prasad, R. (2016). Data collection using miniature aerial vehicles in wireless sensor networks. IET Wireless Sensor Systems, 6(1), 17-25. doi:10.1049/iet-wss.2014.0120Zou, T., Lin, S., Feng, Q., & Chen, Y. (2016). Energy-Efficient Control with Harvesting Predictions for Solar-Powered Wireless Sensor Networks. 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Anti-leishmanial and cytotoxic activities of extracts from three Pakistani plants

Purpose: To evaluate the in vitro and in vivo anti-leishmanial and cytotoxic activities of extracts of different parts of Lawsonia Inermis, Morus nigra and Ziziphus mauritiana.Methods: The methanol extracts of all three plant materials at concentrations of 10 - 100 μg/mL were tested for their in vitro anti-leishmanial effects on L. tropica KWH23 promastigotes for 24 - 48 h, relative to negative control and amphotericin-B (standard drug). For in vivo anti-leishmanial activity, the extracts were tested against L. tropica-infected albino mice, while cytotoxicity was investigated against mammalian cells (lymphocytes).Results: For Lawsonia Inermis leaves, mean inhibition of extracellular promastigotes at 10, 25, 50 and 100 μg/mL after 48 h were 98.2 ± 0.06, 98.75 ± 1.09, 99.31 ± 0.00 and 100.00 ± 0.00 %, respectively. After 8 weeks, mean lesion size decreased from 0.8 ± 0.2 mm to 0.3 ± 0.1 mm (p < 0.01), and cure at 150 mg/kg against intracellular amastigotes in albino mice was 97.02 % (95 % CI = 96.14 - 98.10). IC50 for Lawsonia inermis leaf extract was 12.22 μg/mL (95 % CI = 11.54 - 13.84) against lymphocytes.Conclusion: The results obtained in this study show that Lawsonia Inermis leaf is safe and possesses potent anti-leishmanial activity.Keywords: Leishmania tropica, Lawsonia inermis, Morus Nigra, Ziziphus Mauritiana, Anti-leishmania, Amastigotes, Lymphocyte

Zinc nutrition application augments morpho-physiological attributes, productivity and grain zinc bioavailability of Paddy Rice

Zinc (Zn) deficiency is the most important micronutrient disorders affecting plants and human health. Present study evaluated the potential of various Zn application methods in improving the performance of selected rice genotypes and Zn bioavailability in grains. Pre-selected Zn application methods through pot experiments were validated in the field. Harvested grains were fed to albino rats for Zn bioavailability. Results revealed that soil + foliar application of Zn was effective in improving the seedling growth of rice genotypes by modulating the agronomic, water related and biochemical attributes. The rats gained more body weight fed with rice genotype Accession-164 (high Zn accumulator) compared with the minimum for Super Basmati (low Zn accumulator) feed. In crux, soil application of Zn at 15 kg ha-1 followed by foliar application of 0.25% ZnSO4.7H2O solution at tillering and heading stages produced the highest grain yield (26.25%, 29.11%) with maximum bioavailable Zn (21.02%, 22.50%) during both years, respectively, in the grains for combating malnutrition in the tested rats

A review of NLIDB with deep learning: findings, challenges and open issues

Relational databases are storage for a massive amount of data. Knowledge of structured query language is a prior requirement to access that data. That is not possible for all non-technical personals, leading to the need for a system that translates text to SQL query itself rather than the user. Text to SQL task is also crucial because of its economic and industrial value. Natural Language Interface to Database (NLIDB) is the system that supports the text-to-SQL task. Developing the NLIDB system is a long-standing problem. Previously they were built based on domain-specific ontologies via pipelining methods. Recently a rising variety of Deep learning ideas and techniques brought this area to the attention again. Now end to end Deep learning models is being proposed for the task. Some publicly available datasets are being used for experimentation of the contributions, making the comparison process convenient. In this paper, we review the current work, summarize the research trends, and highlight challenging issues of NLIDB with Deep learning models. We discussed the importance of datasets, prediction model approaches and open challenges. In addition, methods and techniques are also summarized, along with their influence on the overall structure and performance of NLIDB systems. This paper can help future researchers start having prior knowledge of findings and challenges in NLIDB with Deep learning approaches

Detecting wake lock leaks in Android apps using machine learning

The popularity of Android devices has increased exponentially with an increase in the number of mobile devices. Millions of online apps are used in these devices. Energy consumption of a device is a major concern for end-users, who want a long usage time on a single battery charge. The energy consumed by the app must be optimized by developers, and the available APIs must be used carefully. A wake-lock is used in apps to control the power state of the Android device and often leads to energy leakage. In this study, we detected wake-lock leaks in Android apps using machine learning. We pre-processed apps by extracting wake-lock related APIs to obtain the structural information of wake-lock usage and oversampled the data using the synthetic minority oversampling technique (SMOTE) to balance the dataset. The machine learning algorithms used to detect wake-lock leaks were first optimized using grid search to determine the best parameters. These parameters were then used in training to detect wake-lock leaks in these apps. We employed various machine learning algorithms and divided them into simple and ensemble algorithms to evaluate their efficacy. The support vector machine (SVM) and stochastic gradient boosting (SGB) were the most effective, producing 97 % and 98 % accuracy, respectively

Biostimulants Application: An Innovative Approach to Food Security under Drought Stress

Climate change is a global threat to food security as it causes various biotic and abiotic stresses that adversely disturb agriculture production. With an increase in the worldwide population, the demand for food has also arisen. It is an immediate challenge for the scientific community to introduce an innovative tool to achieve food security with quality plant production and develop tolerance against abiotic stresses, specifically drought. Genetically modifications are effective and time-consuming, while biostimulants are in/organic substances with the potential to support plant development under stress conditions. This chapter focuses on the impacts of climate change on agriculture, challenges for agriculture sustainability and food security, the interrelationship between drought, climate change and food security, the potential role of biostimulants against drought, future aspects and challenges due to climate change specifically drought, and food security challenges. Various studies reported that the application of biostimulants results in enhancement of crop productivity and mitigates the harmful effects due to climate change. To ensure the quality of chapter, we collected references from well-reputed international journals using keywords ““biostimulants,” “drought,” “food security,” “agriculture sustainability,” and “climate change.” In conclusion, biostimulants has a potential to address adverse environmental conditions without affecting crop quality and yield loss

A Deployable and Cost-Effective Kirigami Antenna for Sub-6 GHz MIMO Applications

In this work, a low-cost, deployable, integratable, and easy-to-fabricate multiple-input multiple-output (MIMO) Kirigami antenna is proposed for sub-6 GHz applications. The proposed MIMO antenna is inspired by Kirigami art, which consists of four radiating and parasitic elements. The radiating and parasitic elements are composed of a rectangular stub. These elements are placed in such a way that they can provide polarization diversity. The proposed MIMO antenna is designed and fabricated using a soft printed board material called flexible copper-clad laminate (FCCL). It is observed from the results that the proposed MIMO antenna resonates in the 2.5 GHz frequency band, with a 10 dB reflection coefficient bandwidth of 860 MHz ranging from 2.19 to 3.05 GHz. It is worthwhile to mention that the isolation between adjacent radiating elements is higher than 15 dB. In addition, the peak realized gain of the MIMO antenna is around 11 dBi, and the total efficiency is more than 90% within the band of interest. Moreover, the envelope correlation coefficient (ECC) is noted to be less than 0.003, and the channel capacity is ≥17 bps/Hz. To verify the simulated results, a prototype was fabricated, and excellent agreement between the measured and computed results was observed. By observing the performance attributes of the proposed design, it can be said that there are many applications in which this antenna can be adopted. Because of its low profile, it can be used in 5G small-cell mobile MIMO base stations, autonomous light mobility vehicles, and other applications

Forward-central two-particle correlations in p-Pb collisions at root s(NN)=5.02 TeV

Two-particle angular correlations between trigger particles in the forward pseudorapidity range (2.5 2GeV/c. (C) 2015 CERN for the benefit of the ALICE Collaboration. Published by Elsevier B. V.Peer reviewe

Event-shape engineering for inclusive spectra and elliptic flow in Pb-Pb collisions at root(NN)-N-S=2.76 TeV

Peer reviewe