From arsenal delivery to rescue missions, unmanned aerial vehicles (UAVs) are playing a crucial role in various fields, which brings the need for continuous evolution of system identification techniques to develop sophisticated mathematical models for effective flight control. In this paper, a novel parameter estimation technique based on filter error method (FEM) augmented with particle swarm optimisation (PSO) is developed and implemented to estimate the longitudinal and lateral-directional aerodynamic, stability and control derivatives of fixed-wing UAVs. The FEM used in the estimation technique is based on the steady-state extended Kalman filter, where the maximum likelihood cost function is minimised separately using a randomised solution search algorithm, PSO and the proposed method is termed FEM-PSO. A sufficient number of compatible flight data sets were generated using two cropped delta wing UAVs, namely CDFP and CDRW, which are used to analyse the applicability of the proposed estimation method. A comparison has been made between the parameter estimates obtained using the proposed method and the computationally intensive conventional FEM. It is observed that most of the FEM-PSO estimates are consistent with wind tunnel and conventional FEM estimates. It is also noticed that estimates of crucial aerodynamic derivatives ${C_{{L_\alpha }}},\;{C_{{m_\alpha }}},\;{C_{{Y_\beta }}},\;{C_{{l_\beta }}}$ and ${C_{{n_\beta }}}$ obtained using FEM-PSO are having relative offsets of 2.5%, 1.5%, 6.5%, 3.4% and 7.6% w.r.t. wind tunnel values for CDFP, and 1.4%, 1.9%, 0.1%, 9.6% and 7.5% w.r.t. wind tunnel values for CDRW. Despite having slightly higher Cramer-Rao Lower Bounds of estimated aerodynamic derivatives using the FEM-PSO method, the simulated responses have a relative error of less than 0.10% w.r.t. measured flight data. A proof-of-match exercise is also conducted to ascertain the efficacy of the estimates obtained using the proposed method. The degree of effectiveness of the FEM-PSO method is comparable with conventional FEM.

Solving the Arithmetic Word Problems (AWPs) using AI techniques has attracted much attention in recent years. We feel that the current AWP solvers are under-utilizing the relevant domain knowledge. We present a knowledge- and learning-based system that effectively solves AWPs of a specific type—those that involve transfer of objects from one agent to another (Transfer Cases (TC)). We represent the knowledge relevant to these problems as TC Ontology. The sentences in TC-AWPs contain information of essentially four types: before-transfer, transfer, after-transfer, and query. Our system (KLAUS-Tr) uses statistical classifier to recognize the types of sentences. The sentence types guide the information extraction process used to identify the agents, quantities, units, types of objects, and the direction of transfer from the AWP text. The extracted information is represented as an RDF graph that utilizes the TC Ontology terminology. To solve the given AWP, we utilize semantic web rule language (SWRL) rules that capture the knowledge about how object transfer affects the RDF graph of the AWP. Using the TC ontology, we also analyze if the given problem is consistent or otherwise. The different ways in which TC-AWPs can be inconsistent are encoded as SWRL rules. Thus, KLAUS-Tr can identify if the given AWP is invalid and accordingly notify the user. Since the existing datasets do not have inconsistent AWPs, we create AWPs of this type and augment the datasets. We have implemented KLAUS-Tr and tested it on TC-type AWPs drawn from the All-Arith and other datasets. We find that TC-AWPs constitute about 40% of the AWPs in a typical dataset like All-Arith. Our system achieves an impressive accuracy of 92%, thus improving the state-of-the-art significantly. We plan to extend the system to handle AWPs that contain multiple transfers of objects and also offer explanations of the solutions.

We present the pulse arrival times and high-precision dispersion measure estimates for 14 millisecond pulsars observed simultaneously in the 300 $-$ 500 MHz and 1260 $-$ 1460 MHz frequency bands using the upgraded Giant Metrewave Radio Telescope. The data spans over a baseline of 3.5 years (2018-2021), and is the first official data release made available by the Indian Pulsar Timing Array collaboration. This data release presents a unique opportunity for investigating the interstellar medium effects at low radio frequencies and their impact on the timing precision of pulsar timing array experiments. In addition to the dispersion measure time series and pulse arrival times obtained using both narrowband and wideband timing techniques, we also present the dispersion measure structure function analysis for selected pulsars. Our ongoing investigations regarding the frequency dependence of dispersion measures have been discussed. Based on the preliminary analysis for five millisecond pulsars, we do not find any conclusive evidence of chromaticity in dispersion measures. Data from regular simultaneous two-frequency observations are presented for the first time in this work. This distinctive feature leads us to the highest precision dispersion measure estimates obtained so far for a subset of our sample. Simultaneous multi-band upgraded Giant Metrewave Radio Telescope observations in 300 $-$ 500 MHz and 1260 $-$ 1460 MHz are crucial for high-precision dispersion measure estimation and for the prospect of expanding the overall frequency coverage upon the combination of data from the various Pulsar Timing Array consortia in the near future. Parts of the data presented in this work are expected to be incorporated into the upcoming third data release of the International Pulsar Timing Array.

The 4-hydroxyphenylpyruvate dioxygenase (HPPD)-inhibiting herbicides are primarily used for weed control in corn, barley, oat, rice, sorghum, sugarcane, and wheat production fields in the United States. The objectives of this review were to summarize (1) the history of HPPD-inhibitor and their use in the United States, (2) HPPD-inhibitor resistant weeds, their mechanism of resistance, and management, (3) interaction of HPPD-inhibitor with other herbicides, and (4) the future of HPPD-inhibitor-resistant crops. As of 2022, three broadleaf weeds (Palmer amaranth, waterhemp, and wild radish) have evolved resistance to the HPPD-inhibitor. The predominance of metabolic resistance to HPPD-inhibitor was found in aforementioned three weed species. Management of HPPD-inhibitor-resistant weeds can be accomplished using alternate herbicides such as glyphosate, glufosinate, 2,4-D, or dicamba; however, metabolic resistance poses a serious challenge, as the weeds may be cross-resistant to other herbicide sites of action, leading to limited herbicide options. The HPPD-inhibitor is commonly applied with photosystem II (PS II)-inhibitor to increase efficacy and weed control spectrum. The synergism with HPPD-inhibitor arises from depletion of plastoquinones, which allows increased binding of PS II-inhibitor to the D1 protein. New HPPD-inhibitor from azole carboxamides class is in development and expected to be available in the near future. The HPPD-inhibitor-resistant crops have been developed through overexpression of a resistant bacterial HPPD enzyme in plants and the overexpression of transgenes for HPPD and a microbial gene that enhances the production of HPPD substrate. Isoxaflutole-resistant soybean is commercially available, and it is expected that soybean resistant to other HPPD-inhibitor such as mesotrione, stacked with resistance to other herbicides, will be available in the near future.

In this article, we investigate why millions of northern white men volunteered to fight in the Civil War. Prior studies have found that Republican partisanship played a significant role in boosting Union enlistment but do not test the competing hypothesis that views about slavery and race motivated them instead. Such views were highly salient among party elites before and during the war, which was sparked by a presidential election between parties divided over the expansion of Black enslavement. However, among the white mass public, we argue that partisanship rather than race-related attitudes explains patterns of war mobilization. Linking Union war participation records with election returns, we show that county-level war participation is better explained by Republican partisanship rather than views about the status of Black Americans (as measured by support for equal suffrage referenda and the Free Soil party). Analyzing a sample of partisan newspaper issues, we further show that Republican elites de-emphasized slavery as they sought to mobilize mass war participation while antiwar Democrats emphasized antiabolition and white supremacy, suggesting each party’s elites saw antislavery messaging as ineffective or even detrimental in mobilizing mass enlistment. This analysis offers additional evidence on the power of partisanship in producing mass violence and sheds more light on political behavior during a critical period in the history of U.S. racial politics.

Background: MOG-IgG is associated with non-MS demyelinating disease of the optic nerves, spinal cord and brain. Specificity has been issue so we validated the live and fixed MOG-IgG CBAs against the Oxford Autoimmune Neurology Diagnostic Laboratory (OANG) live CBA as a comparator with high specificity. Methods: At BC Neuroimmunology lab (BCNI), 54 MOG-IgG serum samples previously positive by live-CBA at OANG and BCNI were blindly tested by commercial fixed CBA. All 54 MOG IgG positives came from MOG-IgG positive patients. In addition, 256 samples from healthy people and other neurolgic disease were tested. Results: The live MOG-IgG CBA performed at BCNI was 100% concordant (54/54) with OANG live CBA. In contrast, only 49/54 samples were found seropositive by the commercial fixed CBA. The BCNI live-CBA identified 3/256 control samples as positive while 6/256 controls were positive on the fixed commercial CBA. On this cohort the live CBA is 100% sensitive, 98.8% specific and has PPV of 95%. The commercial fixed MOG test is 91% sensitive, 97.6% specific and has PPV of 87.5%. Conclusions: BCNI live MOG-IgG CBAs are in 100% agreement with MOG-IgG. Three positive results in non-MOGAD associated clinical phenotype require further investigation. These data confirm the superiority of the live MOG CBA.

Background: Eye movements reveal neurodegenerative disease processes due to overlap between oculomotor circuitry and disease-affected areas. Characterizing oculomotor behaviour in context of cognitive function may enhance disease diagnosis and monitoring. We therefore aimed to quantify cognitive impairment in neurodegenerative disease using saccade behaviour and neuropsychology. Methods: The Ontario Neurodegenerative Disease Research Initiative recruited individuals with neurodegenerative disease: one of Alzheimer’s disease, mild cognitive impairment, amyotrophic lateral sclerosis, frontotemporal dementia, Parkinson’s disease, or cerebrovascular disease. Patients (n=450, age 40-87) and healthy controls (n=149, age 42-87) completed a randomly interleaved pro- and anti-saccade task (IPAST) while their eyes were tracked. We explored the relationships of saccade parameters (e.g. task errors, reaction times) to one another and to cognitive domain-specific neuropsychological test scores (e.g. executive function, memory). Results: Task performance worsened with cognitive impairment across multiple diseases. Subsets of saccade parameters were interrelated and also differentially related to neuropsychology-based cognitive domain scores (e.g. antisaccade errors and reaction time associated with executive function). Conclusions: IPAST detects global cognitive impairment across neurodegenerative diseases. Subsets of parameters associate with one another, suggesting disparate underlying circuitry, and with different cognitive domains. This may have implications for use of IPAST as a cognitive screening tool in neurodegenerative disease.

Aedes-borne diseases are on the rampant rise despite continued application of chemical insecticide-based interventions. The appearance of high degree of insecticide resistance in Aedes species and noxious effects on environment and non-targets have raised further concerns. Among new chemical interventions, neonicotinoids are considered a safe and effective approach. The present study investigated the control potency of acetamiprid and development of resistance in Aedes aegypti larvae; and the involvement of CYP450 monooxygenases in inducing resistance. The early fourth instars of Ae. aegypti parent susceptible strain (PS) were selected with acetamiprid for 15 generations (ACSF strain) increasing the resistance to 19.74-fold in ACSF-10 and 36.71-fold in ACSF-15. The ACSF-10 larvae were assayed with acetamiprid combined with piperonyl butoxide (PBO) in three different ratios (1:1, 1:5 and 1:10) and selected for next five generations with 1:10 combination. Selection with synergized acetamiprid (APSF strains) reversed as well as reduced the rate of resistance development resulting in only 1.35-fold resistance in APSF-15. The APSF strains showed %monooxygenase dependency ranging from 86.71 to 96.72%. The estimation of the monooxygenases levels in parent and selected larvae showed increased monooxygenase level in the ACSF strains by 2.42–2.87-fold. The APSF-15 strains exhibited 57.95% lower enzyme production than ACSF-15 strain. The reduction and reversion of resistance by using PBO and the elevated levels of monooxygenases in ACSF and reduction in APSF strains recommend the involvement of CYP450-mediated mechanism in the development of acetamiprid resistance in Ae. aegypti. These studies could help in devising resistance management strategies in order to preserve the efficiency of pre-existing insecticides.

Anthracnose caused by Colletotrichum truncatum is a major soybean disease in India. Genetic resistance is the viable option to combat yield losses due to this disease. In the current study, 19 soybean genotypes were evaluated for anthracnose disease resistance at five locations (Medziphema, Palampur, Dharwad, Jabalpur and Indore) for three consecutive years (2017–2019) to identify stable and superior genotypes as resistant sources and to elucidate genotype (G) × environment (E) interactions. Genotype effect, environment effect and G × E interactions were found significant (P < 0.001) where G × E interactions contributed highest (42.44) to the total variation followed by environment (29.71) and genotype (18.84). Through Weighted Average of Absolute Scores (WAASB) stability analysis, PS 1611 (WAASB score = 0.33) was found to be most stable and through WAASBY superiority analysis NRC 128 (WAASBY score = 94.31) and PS 1611 (WAASBY score = 89.43) were found to be superior for mean performance and stability. These two genotypes could be candidate parents for breeding for durable and stable anthracnose resistance. Through principal component analysis, disease score was found to be positively associated with relative humidity, wind speed at 2 m above ground level, effect of temperature on radiation use efficiency and global solar radiation based on latitude and Julian day. Among the five locations, Indore was found to be highly discriminative with the highest mean disease incidence and could differentiate anthracnose-resistant and susceptible genotypes effectively, therefore can be considered an ideal location for breeding for field resistance against anthracnose disease.

Weeds are a major biotic constraint to the production of crops. Studies on the critical period of weed control (CPWC) consider the yield loss due to the presence of all weeds present in the crop cycle. The CPWC is the time interval between the critical timing of weed removal (CTWR) and the critical weed-free period (CWFP), and the weed presence before and after the extremes of CTWR and CWFP may not significantly reduce crop yield. The crop yield is taken into consideration and weed density or biomass of individual weeds (annual or perennial) is not so important while calculating the CPWC. Only weed density or biomass is considered for calculating weed control efficiency of a particular management practice for which the weed seed bank is also a criterion. However, weed biomass is the outcome after competition experienced by each weed species with the fellow crop and the weeds. Consequently, the weed pressure in the subsequent season will be the cumulative effect of the preceding season too, which is unaccounted for in CPWC. It is argued that in organic farming or low-input farming systems, where herbicides are not used, the concept of CPWC can be misleading and should be avoided. It is concluded that CTWR is more meaningful than the CPWC.