Internet of things (IoT) assisted soil salinity mapping at irrigation schema level

Soil salinity accumulates a high concentration of salts in soils that interfere with normal plant growth. Early detection and quantification of soil salinity are essential to effectively deal with soil salinity in agriculture. Soil salinity quantification and mapping at the irrigation scheme level are vital to evaluating saline soil's reclamation activity. Existing solutions of salinity mapping are costly, time-consuming, and inadequate for applications at the irrigation scheme level. Internet of Things (IoT) assisted salinity mapping at the irrigation scheme level is proposed to quantify and map the soil salinity in agriculture. The proposed IoT-assisted salinity mapping characterizes the soil salinity in terms of Electric Conductivity, pH, and Total Dissolved Salts. The proposed IoT-assisted salinity mapping effectively observes impacts of reclamation activities in saline soil by frequent observation of soil salinity cost-effectively. The accuracy of proposed IoT-assisted salinity mapping is evaluated against the standard method of salinity measurements. The proposed IoT-assisted salinity mapping is cost-effective, and portable, which is very useful for site-specific treatments and soil zones management in saline soils

High prevalence of vitamin D deficiency among women of child-bearing age in Lahore Pakistan, associating with lack of sun exposure and illiteracy

BACKGROUND: Vitamin D status is a key determinant of maternal and neonatal health. Deficiency has been reported to be common in Pakistani women, but information regarding environmental and genetic determinants of vitamin D status is lacking in this population. METHODS: We conducted a cross-sectional study among three groups of healthy women living in Lahore, Pakistan: university students, students or employees of Medrasas or Islamic Institutes, and employees working in office, hospital or domestic settings. Multivariate analysis was performed to identify environmental and genetic determinants of vitamin D status: polymorphisms in genes encoding the vitamin D receptor, vitamin D 25-hydroxylase enzyme CYP2R1 and vitamin D binding protein [DBP] were investigated. We also conducted analyses to identify determinants of body ache and bone pain in this population, and to determine the sensitivity and specificity of testing for hypocalcaemia and raised serum alkaline phosphatase to screen for vitamin D deficiency. RESULTS: Of 215 participants, 156 (73 %) were vitamin D deficient (serum 25[OH]D <50 nmol/L). Risk of vitamin D deficiency was independently associated with illiteracy (adjusted OR 4.0, 95 % CI 1.03–15.52, P = 0.04), <30 min sun exposure per day (adjusted OR 2.13, 95 % CI 1.08–4.19, P = 0.02), sampling in January to March (adjusted OR 2.38, 95 % CI 1.20–4.70), P = 0.01) and lack of regular intake of multivitamins (adjusted OR 2.61, 95 % CI 1.32–5.16, p = 0.005). Participants with the GG genotype of the rs4588 polymorphism in the gene encoding vitamin D binding protein tended to have lower 25(OH)D concentrations than those with GT/TT genotypes (95 % CI for difference 22.7 to −0.13 nmol/L, P = 0.053). Vitamin D deficiency was independently associated with increased risk of body ache or bone pain (adjusted OR 4.43, 95 % CI 2.07 to 9.49, P = 0.001). Hypocalcaemia (serum calcium concentration ≤9.5 mg/dL) and raised alkaline phosphatase concentration (≥280 IU/L) had low sensitivity and very low specificity for identification of vitamin D deficiency. CONCLUSION: Vitamin D deficiency is common among healthy women of child-bearing age in Lahore, Pakistan: illiteracy, decreased sun exposure and lack of multivitamin intake are risk factors

Identification of the Bovine Arachnomelia Mutation by Massively Parallel Sequencing Implicates Sulfite Oxidase (SUOX) in Bone Development

Arachnomelia is a monogenic recessive defect of skeletal development in cattle. The causative mutation was previously mapped to a ∼7 Mb interval on chromosome 5. Here we show that array-based sequence capture and massively parallel sequencing technology, combined with the typical family structure in livestock populations, facilitates the identification of the causative mutation. We re-sequenced the entire critical interval in a healthy partially inbred cow carrying one copy of the critical chromosome segment in its ancestral state and one copy of the same segment with the arachnomelia mutation, and we detected a single heterozygous position. The genetic makeup of several partially inbred cattle provides extremely strong support for the causality of this mutation. The mutation represents a single base insertion leading to a premature stop codon in the coding sequence of the SUOX gene and is perfectly associated with the arachnomelia phenotype. Our findings suggest an important role for sulfite oxidase in bone development

The Merging of Two Dynasties—Identification of an African Cotton Leaf Curl Disease-Associated Begomovirus with Cotton in Pakistan

Cotton leaf curl disease (CLCuD) is a severe disease of cotton that occurs in Africa and Pakistan/northwestern India. The disease is caused by begomoviruses in association with specific betasatellites that differ between Africa and Asia. During survey of symptomatic cotton in Sindh (southern Pakistan) Cotton leaf curl Gezira virus (CLCuGV), the begomovirus associated with CLCuD in Africa, was identified. However, the cognate African betasatellite (Cotton leaf curl Gezira betasatellite) was not found. Instead, two Asian betasatellites, the CLCuD-associated Cotton leaf curl Multan betasatellite (CLCuMB) and Chilli leaf curl betasatellite (ChLCB) were identified. Inoculation of the experimental plant species Nicotiana benthamiana showed that CLCuGV was competent to maintain both CLCuMB and ChLCB. Interestingly, the enations typical of CLCuD were only induced by CLCuGV in the presence of CLCuMB. Also in infections involving both CLCuMB and ChLCB the enations typical of CLCuMB were less evident. This is the first time an African begomovirus has been identified on the Indian sub-continent, highlight the growing threat of begomoviruses and particularly the threat of CLCuD causing viruses to cotton cultivation in the rest of the world

Political connections and corporate financial decision making

This paper investigates whether and how political connections influence managerial financial decisions. Our study reveals that those firms that have a politician on its board of directors are highly leveraged, use more long-term debt, hold large excess cash and are associated with low quality financial reporting compared to their non-connected counterparts. These effects escalate with the strength of the connected politician and whether he or his party is in power. The winning party effect is observed to be stronger than victory by the politician himself. Overall, our paper provides strong evidence that political connection is a two-edged sword. It is indeed a valuable resource for connected firms, but it comes at a cost of higher agency problems

Wind Power Persistence Characterized by Superstatistics

Mitigating climate change demands a transition towards renewable electricity generation, with wind power being a particularly promising technology. Long periods either of high or of low wind therefore essentially define the necessary amount of storage to balance the power system. While the general statistics of wind velocities have been studied extensively, persistence (waiting) time statistics of wind is far from well understood. Here, we investigate the statistics of both high- and low-wind persistence. We find heavy tails and explain them as a superposition of different wind conditions, requiring q-exponential distributions instead of exponential distributions. Persistent wind conditions are not necessarily caused by stationary atmospheric circulation patterns nor by recurring individual weather types but may emerge as a combination of multiple weather types and circulation patterns. This also leads to Fréchet instead of Gumbel extreme value statistics. Understanding wind persistence statistically and synoptically may help to ensure a reliable and economically feasible future energy system, which uses a high share of wind generation

The Rate of Recurrence of Club Foot Deformity in Patients Using Dennis Brown Splint

Objective: To estimate the rate of recurrence of deformity in patients using Dennis Brown Splint and for the description of the issues related to non-compliance of the Dennis Brown Splint. Material and Methods: It was a prospective descriptive case series study.70 patients with corrected Club Feet were selected from APPNA Rehabilitation Department of Benazir Bhutto Hospital. The patients were given the Dennis Brown Splints for the maintenance of the correction followed by Ponseti method. Clubfeet were graded according to the Pirani scoring system check the recurrence of the deformity. Patients were called for routine follow-up to check the rate of recurrence of the deformity and parents were interviewed for the issues related to non-compliance to the bracing program. Duration of the study was 12 months followed by the bracing. Results: It is founded that the recurrence of the deformity is about 24%. 17/70 reported with recurrence with the deformity after correction during bracing program. While the issues of non-compliance 47% reported with skin problems while 45% reported with residual adduction of the foot part due to loosening of the screw. 30 % reported that their babies withdraw the foot from the shoes by applying force. 70% of the families don’t have even basic education which also adds to the poor outcomes. Conclusion: It was concluded that relapse rate is 24% because of the issues related to the non-compliance from which main issue is skin damage. The second other cause is repeated residual adduction due to the loosening of the screw. Most of the families have very low education so it was founded very difficult to counsel them. Some families also quit from bracing without informing the consultants

An accelerated particle swarm optimization based levenberg marquardt back propagation algorithm

The Levenberg Marquardt (LM) algorithm is one of the most effective algorithms in speeding up the convergence rate of the Artificial Neural Networks (ANN) with Multilayer Perceptron (MLP) architectures. However, the LM algorithm suffers the problem of local minimum entrapment. Therefore, we introduce several improvements to the Levenberg Marquardt algorithm by training the ANNs with meta-heuristic nature inspired algorithm. This paper proposes a hybrid technique Accelerated Particle Swarm Optimization using Levenberg Marquardt (APSO_LM) to achieve faster convergence rate and to avoid local minima problem. These techniques are chosen since they provide faster training for solving pattern recognition problems using the numerical optimization technique.The performances of the proposed algorithm is evaluated using some bench mark of classification&rsquo;s datasets. The results are compared with Artificial Bee Colony (ABC) Algorithm using Back Propagation Neural Network (BPNN) algorithm and other hybrid variants. Based on the experimental result, the proposed algorithms APSO_LM successfully demonstrated better performance as compared to other existing algorithms in terms of convergence speed and Mean Squared Error (MSE) by introducing the error and accuracy in network convergence