Planting Geometry and Herbicides for Weed Control in Rice: Implications and Challenges

Weeds are one of the major biological threats to higher rice productivity worldwide. Various cultural, biological, physical and chemical practices affect the composition and intensity of weeds in rice fields. Generally, weeds can be controlled through herbicides; nevertheless, chemical weed control is not a sustainable option on a long term. Various agronomic practices such as the use of tolerant cultivars, adjusting sowing time, tillage permutations and plant geometry may reduce the weed pressure in rice. Integrated approaches for weed management, emphasizing on the combination of management practices and scientific knowledge, may reduce the economic costs and improve weed control owing to the complexity of the weed community. The present chapter reveals the role of planting geometry and herbicides as weed management strategies in rice, and discusses the issue of herbicide resistance associated with chemical weed control. Moreover, the research and knowledge gaps in rice weed management through planting geometry and herbicides were also highlighted

Biallelic Variants in Seven Different Genes Associated with Clinically Suspected Bardet-Biedl Syndrome

Bardet-Biedl syndrome (BBS) is a rare clinically and genetically heterogeneous autosomal recessive multi-systemic disorder with 22 known genes. The primary clinical and diagnostic features include six different hallmarks, such as rod-cone dystrophy, learning difficulties, renal abnormalities, male hypogonadism, post-axial polydactyly, and obesity. Here, we report nine consanguineous families and a non-consanguineous family with several affected individuals presenting typical clinical features of BBS. In the present study, 10 BBS Pakistani families were subjected to whole exome sequencing (WES), which revealed novel/recurrent gene variants, including a homozygous nonsense mutation (c.94C>T; p.Gln32Ter) in the IFT27 (NM_006860.5) gene in family A, a homozygous nonsense mutation (c.160A>T; p.Lys54Ter) in the BBIP1 (NM_001195306.1) gene in family B, a homozygous nonsense variant (c.720C>A; p.Cys240Ter) in the WDPCP (NM_015910.7) in family C, a homozygous nonsense variant (c.505A>T; p.Lys169Ter) in the LZTFL1 (NM_020347.4) in family D, pathogenic homozygous 1 bp deletion (c.775delA; p.Thr259Leufs*21) in the MKKS/BBS5 (NM_170784.3) gene in family E, a pathogenic homozygous missense variant (c.1339G>A; p.Ala447Thr) in BBS1 (NM_024649.4) in families F and G, a pathogenic homozygous donor splice site variant (c.951+1G>A; p?) in BBS1 (NM_024649.4) in family H, a pathogenic bi-allelic nonsense variant in MKKS (NM_170784.3) (c.119C>G; p.Ser40*) in family I, and homozygous pathogenic frameshift variants (c.196delA; p.Arg66Glufs*12) in BBS5 (NM_152384.3) in family J. Our findings extend the mutation and phenotypic spectrum of four different types of ciliopathies causing BBS and also support the importance of these genes in the development of multi-systemic human genetic disorders

A technical perspective on integrating artificial intelligence to solid-state welding

The implementation of artificial intelligence (AI) techniques in industrial applications, especially solid-state welding (SSW), has transformed modeling, optimization, forecasting, and controlling sophisticated systems. SSW is a better method for joining due to the least melting of material thus maintaining Nugget region integrity. This study investigates thoroughly how AI-based predictions have impacted SSW by looking at methods like Artificial Neural Networks (ANN), Fuzzy Logic (FL), Machine Learning (ML), Meta-Heuristic Algorithms, and Hybrid Methods (HM) as applied to Friction Stir Welding (FSW), Ultrasonic Welding (UW), and Diffusion Bonding (DB). Studies on Diffusion Bonding reveal that ANN and Generic Algorithms can predict outcomes with an accuracy range of 85 – 99%, while Response Surface Methodology such as Optimization Strategy can achieve up to 95 percent confidence levels in improving bonding strength and optimizing process parameters. Using ANNs for FSW gives an average percentage error of about 95%, but using metaheuristics refined it at an incrementally improved accuracy rate of about 2%. In UW, ANN, Hybrid ANN, and ML models predict output parameters with accuracy levels ranging from 85 to 96%. Integrating AI techniques with optimization algorithms, for instance, GA and Particle Swarm Optimization (PSO) significantly improves accuracy, enhancing parameter prediction and optimizing UW processes. ANN’s high accuracy of nearly 95% compared to other techniques like FL and ML in predicting welding parameters. HM exhibits superior precision, showcasing their potential to enhance weld quality, minimize trial welds, and reduce costs and time. Various emerging hybrid methods offer better prediction accuracy

Clinical practice guidelines on the management of variceal bleeding

Gastroesophageal variceal bleeding occurs in 30 - 50% of patients of liver cirrhosis with portal hypertension, with 20-70% mortality in one year. Therefore, it is essential to screen these patients for varices and prevent first episode of bleeding by treating them with β-blockers or endoscopic variceal band ligation. Ideally, the patients with variceal bleeding should be treated in a unit where the personnel are familiar with the management of such patients and where routine therapeutic interventions can be undertaken. Proper management of such patients include: initial assessment, resuscitation, blood volume replacement, vasoactive agents, prevention of associated complications such as bacterial infections, hepatic encephalopathy, coagulopathy and thrombocytopenia, and specific therapy. Rebleeding occurs in about 60% patients within 2 years of their recovery from first variceal bleeding episode, with 33% mortality. Therefore, it is mandatory that all such patients must be started on combination of β-blockers and band ligation to prevent recurrence of bleeding. Patients who required shunt surgery/TIPSS to control the acute episode do not require further preventive measures. These clinical practice guidelines (CPGs) have been jointly developed by Pakistan Society of Hepatology (PSH) and Pakistan Society of Study of Liver Diseases (PSSLD)

Characterization of the Effect of Increased Plant Density on Canopy Morphology and Stalk Lodging Risk

Plants react to the environment and to management interventions by undergoing architectural and structural modifications. A field trial was conducted in China in 2016 to study the effects of the plant population on morphological development of the maize canopy. The main objectives of the current study were (i) to characterize the effects of increased plant density on canopy morphology and stalk lodging and (ii) to explore the relationships between organ morphology and stalk lodging. The field experiment was composed of five plant densities (4.5, 6, 7.5, 9, and 15 plants m−2) of three cultivars: Zhengdan 958 (lodging-resistant cultivar), Longping 206 and Jinqiu 119 (lodging-susceptible cultivars). In response to plant densities of all the three cultivars, the lamina and sheath lengths increased in lower phytomers but decreased in upper phytomers. The lamina width and internode diameter decreased for all phytomers in response to plant densities for all the cultivars. The correlation between organ morphology, plant density and stalk lodging was linear. Data obtained from characterization used in this study (that is, canopy morphology, correlation of organ morphology with stalk lodging traits in response to various plant densities for different cultivars, etc.) will be useful in future modeling studies to predict the morphology characteristics of the canopy affected by interplant competition and stalk lodging

Development and Exploitation of KASP Assays for Genes Underpinning Drought Tolerance Among Wheat Cultivars From Pakistan

High-throughput genotyping for functional markers offers an excellent opportunity to effectively practice marker-assisted selection (MAS) while breeding cultivars. We developed kompetitive allele-specific PCR (KASP) assays for genes conferring drought tolerance in common wheat (Triticum aestivum L.). In total, 11 KASP assays developed in this study and five already reported assays were used for their application in wheat breeding. We investigated alleles at 16 loci associated with drought tolerance among 153 Pakistani hexaploid wheat cultivars released during 1953–2016; 28 diploid wheat accessions (16 for AA and 12 for BB) and 19 tetraploid wheat (AABB) were used to study the evolutionary history of the studied genes. Superior allelic variations of the studied genes were significantly associated with higher grain yield. Favored haplotypes of TaSnRK2.3-1A, TaSnRK2.3-1B, TaSnRK2.9-5A, TaSAP-7B, and TaLTPs-1A predominated in Pakistani wheat germplasm indicating unconscious pyramiding and selection pressure on favorable haplotypes during selection breeding. TaSnRK2.8-5A, TaDreb-B1, 1-feh w3, TaPPH-7A, TaMOC-7A, and TaPARG-2A had moderate to low frequencies of favorable haplotype among Pakistani wheat germplasm pointing toward introgression of favorable haplotypes by deploying functional markers in marker-assisted breeding. The KASP assays were compared with gel-based markers for reliability and phenotypically validated among 62 Pakistani wheat cultivars. Association analyses showed that the favorable allelic variations were significantly associated with grain yield-contributing traits. The developed molecular marker toolkit of the genes can be instrumental for the wheat breeding in Pakistan

Impact of Sensor Networks on Aquatic Biodiversity in Wetland: An Innovative Approach

Aquatic biodiversity is in the central field of environmental conservation issues in a wetland. Yet it determinately faced aquatic conservation authorities the loss of biodiversity as a very important global issue for several years due to misuse wireless sensor technology. The study attempts to re-look at the sensor networks that affect the aquatic biodiversity within and around the Tanguar Haor- wetland study at Sunamganj district in Bangladesh. Key aquatic conservation tools provided at the Tanguar Haor and its challenges with gaps in policies for wetland management practices are highlighted. The study shows the aquatic biodiversity-related rules and regulations amended were apex in Bangladesh from 2010 to 2018. The study represents the impact of processed sensor networks on aquatic biodiversity in a wetland to be compared to larger, medium, and smaller animals in a bright, dark and optimum environment, facilitating the design and misuse of wireless sensor networks within GPS locations. Approximately 64% of the respondents agreed on the development of aquatic biodiversity for managing the wetland at Sunamganj with secure peripheral sensor networks. The research also found that the Tanguar Haor is at risk due to misuse of wireless sensor networks compared to other wetlands in the Sylhet Division. Scientific knowledge is indispensable in wetland resource management but it poorly identified such knowledge while various performances are still below par. The research is unique and represents the innovative idea to improve the existing wetland policy linking with the appropriateness for the Ramsar Wetland Conservation Strateg

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions