Explore the vast range of titles available.

Growth and development of cereal crops are linked to weather, day length and growing degree-days (GDDs) which make them responsive to the specific environments in specific seasons. Global temperature is rising due to human activities such as burning of fossil fuels and clearance of woodlands for building construction. The rise in temperature disrupts crop growth and development. Disturbance mainly causes a shift in phenological development of crops and affects their economic yield. Scientists and farmers adapt to these phenological shifts, in part, by changing sowing time and cultivar shifts which may increase or decrease crop growth duration. Nonetheless, climate warming is a global phenomenon and cannot be avoided. In this scenario, food security can be ensured by improving cereal production through agronomic management, breeding of climate-adapted genotypes and increasing genetic biodiversity. In this review, climate warming, its impact and consequences are discussed with reference to their influences on phenological shifts. Furthermore, how different cereal crops adapt to climate warming by regulating their phenological development is elaborated. Based on the above mentioned discussion, different management strategies to cope with climate warming are suggested.

Orthogonal frequency division multiplexing (OFDM) is a promising solution for underwater acoustic communication (UWA); however, it requires careful handling of the challenges of large multipath and severe Doppler effects inherent in underwater acoustic communication. This paper proposes a novel feedforward backpropagated neural network (FBNN) implementation for Doppler scaling estimation using UWA cyclic-prefix (CP) OFDM communication. A two-layered input-output feedforward network is utilized with three different backpropagated training algorithm variants: Fletcher-Reeves Conjugate Gradient (CGF), Polak-Ribiére Conjugate Gradient (CGP), and Conjugate Gradient with Powell/Beale Restarts (CGB). The proposed approach calculates the Doppler scale factor by combining the neural computational power with the accuracies offered by the three training algorithms. To evaluate the effectiveness of the proposed FBNN implementation, root mean square error (RMSE) is used as a performance metric for different multipath and signal-to-noise ratio (SNR) channel conditions. The paper also presents a comparison of the proposed FBNN-based training algorithms’ performance with that of the benchmark offered by conventional methods.

Zinc (Zn) deficiency can severely inhibit plant growth, yield, and enzymatic activities. Zn plays a vital role in various enzymatic activities in plants. Arbuscular mycorrhizal fungi (AMF) play a crucial role in improving the plant’s Zn nutrition and mitigating Zn stress effects on plants. The current study was conducted to compare the response of inoculated and non-inoculated maize (YH 1898) in the presence of different levels of zinc under greenhouse conditions under a Zn deficient condition. There were two mycorrhizal levels (i.e., M + with mycorrhizae, M- without mycorrhizae) and five Zn levels (i.e., 0, 1.5, 3, 6, and 12 mg kg -1 ), with three replicates following completely randomized design. At the vegetative stage (before tillering), biochemical, physiological, and agronomic attributes were measured. The results showed that maize plants previously inoculated with AMF had higher gaseous exchange traits, i.e., a higher stomatal conductance rate, favoring an increased photosynthetic rate. Improvement in antioxidant enzyme activity was also observed in inoculated compared to non-inoculated maize plants. Moreover, AMF inoculation also played a beneficial role in nutrients availability and its uptake by plants. Higher Zn12 (12 mg Zn kg -1 soil) treatment accumulated a higher Zn concentration in soil, root, and shoot in AMF-inoculated than in non-inoculated maize plants. These results are consistent with mycorrhizal symbiosis beneficial role for maize physiological functioning in Zn deficient soil conditions. Additionally, AMF inoculation mitigated the stress conditions and assisted nutrient uptake by maize.

The effectiveness of public-sector agricultural development projects in developing countries lies not only in their contributions to agricultural sector growth but also in their contributions to environmental and socioeconomic system growth. As a result, the challenges associated with project procurement and supply chain management need to be carefully analyzed and evaluated. Although there has been reasonable literature on procurement and supply chain management, the limitations include the following: The literature, especially focusing on the analytical methodology, is scarce, as is the case with the developing country public-sector project context. This study, in its own modest way, contributes to this gap. Thus, the goal of this paper is to critically examine the Delphi and/or analytical hierarchy process (AHP), as well as their application and appropriateness in analyzing the challenges in the Bangladesh context, from relevant literature published between 2000 and 2019. A systematic review was carried out using the ABI/Inform, EBSCO, Google Scholar, and Science Direct databases for the study. The review of 2071 articles yielded 37 articles for the study. The Delphi and/or AHP were the most applied tools found in the review. Finally, the study examined 18 articles that applied Delphi and/or AHP methods. The review findings contribute to the literature by providing academics and practitioners with an understanding of the appropriateness of the Delphi-based AHP research framework for analyzing challenges to procurement and supply chain management in public-sector agriculture projects. Following that, a novel best-practice research framework based on the Delphi–AHP method is presented.

Malnutrition a health disorders arising due to over or low use of minerals, vitamins and nutritional substances required for proper functioning of body tissues and organs. Zinc (Zn) is the most important mineral required for the normal metabolism of plants and humans. Zinc-deficiency is one of the major cause of malnutrition globally. Maize is highly susceptible to Zn-deficiency and inflicts Zn-deficiency to humans and other animals being nourished on it. This study evaluated the effect of zinc-lysine chelate alone (0.1, 0.5, 1.0 and 1.5%) as seed priming and in combination with Zn-solubilizing bacteria (PMEL-1, PMEL-48, PMEL-57and PMEL-71)) on grain biofortification of autumn maize. The Zn accumulation in different parts (roots, stem, leaves, grains and cob pith) was quantified. Results indicated that Zn contents were 18.5% higher in the seeds primed with 1.5% solution of Zn-lysine chelate and inoculation of ZSB strains compared to control treatments. Seed priming with 1.5% Zn-lysine chelate in combination with ZSB inoculation significantly improved cob diameter and cob length by 16.75% and 42% during 2016 and by 11.36% and 34.35% during 2017. The increase in 100 grains weight over control was 18.4% and 15.27% for 2016 and 2017, respectively. The Zn contents were increased by 15.3%, 15.6%, 49.1%, and 33.0% in grain, cob-pith, stemand roots, respectively compared from control. Thus, the combined application of 1.5% Zn-lysine chelates along with ZSB inoculation could be used for combating malnutrition.

Magneto-inductive (MI) waveguide technology is often proposed to increase the MI communication distance without adding significant cost and power consumption to the wireless sensor network. The idea is to add intermediate relaying nodes between transmitter (Tx) and receiver (Rx) to relay the information from Tx to Rx. Our study of MI wave-guides has realized that adding a relay node improves the communication distance, however, the performance is greatly dependent on the position of the relaying node in the network. We therefore, in this work have investigated the effect of placement of a relay node and have determined the optimal relay position. We have performed various sets of experiments to thoroughly understand the behavior and identified three main regions: (a) for region 1, when the distance between Tx and Rx is equal or less than the diameter of the coils ( d ≤ 2 r ), the optimal relay position is close to Tx, (b) for region 2, when the distance between Tx and Rx is greater than diameter of the coils but less than twice the diameter ( 2 r < d < 4 r ), the optimal relay position lies in the center of Tx and Rx, and (c) for region 3, when the distance between the Tx and Rx is equal or greater than twice the diameter of the coils ( d ≥ 4 r ), the optimal relay position is close to Rx.

Purpose The purpose of this paper is to examine how corporate governance instruments impact firm value in the context of Pakistan. This paper considers state- and non-state-owned enterprises and examines whether the influence of corporate governance on firm value varies across firms having different nature of ownership. Design/methodology/approach This study opts for an unbalanced sample of state- and non-state-owned enterprises for the period 2010-2014. Panel data regression is adopted for estimation of main results. The suitable model, i.e. fixed and random effect model, is selected using Hausman specification test. Findings The notable findings show that board independence has a significant and positive relationship with firm value only for state-owned companies. Furthermore, the results show that market capitalization and return on assets have a significant and positive association with firm value for both state- and non-state-owned enterprises. All other variables are found insignificant for both state- and non-state-owned companies, but the results are consistent with those reported in previous studies. Practical implication The findings of the study suggest that fair induction of independent directors, appropriate board size and cost-benefit analysis to conduct frequent meetings can help corporations to improve their performance. Originality/value This study is adding to the current literature by providing new insights and shows that the impact of corporate governance on firm value varies across firms of different types of ownership, i.e. state- and non-state-owned enterprises.

PurposeThe purpose of this study is to investigate the impact of COVID-19 on conventional and Islamic stocks by using the data spanning from February 25, 2020, to February 3, 2021, and employing a panel regression approach.Design/methodology/approachIn this study a panel regression approach has been used.FindingsThe study finds a negative association between COVID-19 and stock (both Islamic and conventional). After splitting the data into 1st and 2nd waves, the relationship between COVID-19 and stock (both Islamic and conventional) remains the same (negative) in the case of the 1st wave. In contrast, in the case of the 2nd wave, the relationship turned out to be positive. During both waves of the pandemic, the magnitude of the effect is found to be higher for conventional stocks. Additionally, the study also analyzes the aggregate influence of COVID-19 on different sectors and finds that commercial banks, oil and gas exploration and marketing companies are the most influenced sectors. At the same time, automobiles and pharma are the least affected sectors.Practical implicationsThe study suggests that markets start gaining momentum to reach their prepandemic level after absorbing the initial shock (emergence of a pandemic). The study also provides thorough insights for market regulators and policymakers by implying the dynamic relations between markets (conventional and Islamic) and financial crisis, which would allow them more effective control of crisis in future endeavors.Originality/valueThis is one of the first studies to investigate the impact of COVID-19 on both conventional and Islamic stocks, especially in the context of Pakistan.

This study aims to investigate the supply chain challenges of public sector agriculture development projects in Bangladesh using the modified Delphi, Best Worst Method (BWM), and Interpretive Structural Modelling (ISM) methods. Based on these three widely acclaimed statistical techniques, the study identified, ranked, and identified interrelationships among the challenges. The study is unique not only in terms of research findings, but also in terms of methodology, as it is the first to use the three MCDM (Multicriteria Decision Making) tools to examine supply chain issues in public sector agriculture development projects in a developing country context. A literature review and two modified Delphi rounds with 15 industry experts’ opinions were applied to identify and validate a list of 11 key supply chain challenges. To determine the priority of the challenges, a panel of eight industry experts was consulted, and their responses were analysed using the BWM. Then, another group of 10 experts was consulted using ISM to investigate the contextual relationships among the challenges, resulting in a five-layered Interpretive Structural Model (ISM) and MICMAC (cross-impact matrix multiplication applied to classification) analysis of the challenges. According to relative importance (global weights), \"improper procurement planning (0.213), \"delay in project initiation (0.177), \"demand forecasting error (0.146)\", \"lack of contract monitoring mechanism (0.097)\", and \"lack of competent staff (0.095)\" are the top five ranked key challenges that have a significant impact on the project supply chain. Regarding contextual relationships, the ISM model and ISM-MICMAC analysis identified the \"political influence\" challenge as the most influential, and also independent of the other challenges. The findings are critical for project managers in managing challenges because understanding both relative importance and contextual relationships are required to address the challenges holistically. Additionally, these findings will benefit policymakers, academics, and future researchers.

This study aims to investigate the influence of institutional capacity on the relationship between financial development and environmental quality and also examines the moderating role of corruption on the link between institutional quality and environmental quality. By using yearly data from 33 developing countries for 7 years from 2011 to 2017, this paper applies a dynamic technique system GMM. The results suggest that financial development increases environmental degradation due to possible higher energy-intensive investment. However, institutional capacity moderates its impact on environmental quality by channelizing the funds to energy-efficient investment. The findings of this study suggest that financial development improves the environmental quality when institutional capacity is higher than 3.5 on the scale of 0 to 6. Interestingly, institutional capacity is unable to control environmental degradation in the presence of corruption. The results propose that financial development has a positive relation with environmental degradation in the presence of corruption. Nevertheless, relationship between institutional capacity and environmental degradation turns to negative when corruption improves in the economies. Furthermore, the findings show that institutional capacity may only control environmental degradation when corruption improves to 40 or higher on a scale of 0 to 100. The policy implications of this study are useful for policy departments, environmental regulatory bodies, and financial institutions.