New-onset diabetes mellitus in patients with COVID19 infection admitted to a tertiary care hospital: A single-center experience.

Objective: To determine the frequency of new-onset diabetes mellitus (NODM) in patients with COVID-19 in a tertiary care hospital. Method: It was a retrospective descriptive study carried out in Lady Reading Hospital Peshawar, Khyber Pakhtunkhwa province of Pakistan from November 2021 to April 2022. All patients having new onset Diabetes Mellitus (NODM) were identified among a total of 300 patients admitted to the hospital with COVID-19 infection. Patients' data including relevant investigations were accessed through the hospital management information system (HMIS). SPSS version-23 was used for data entry and statistical analysis. Results: Out of 300 COVID-19 patients included in the study, 163 (54.3%) were female and 137(45.7%) were male. The mean age of the patients was 56.80±13.72 (IQR 15) years. Frequency of the new onset diabetes was 44(14.7%); 19 (6.33%) male and 25(8.33%) female. Among the 44 NODM patients, the majority (57%) were female (p=0.720). Most (64%) of the patients with new-onset DM were in the middle age (p=0.018). Conclusion: A significant number of patients with COVID-19 infection are prone to develop new-onset diabetes during their admission to the hospital.

Synthesis, DFT Studies, Molecular Docking and Biological Activity Evaluation of Thiazole-Sulfonamide Derivatives as Potent Alzheimer's Inhibitors.

Alzheimer's disease is a major public brain condition that has resulted in many deaths, as revealed by the World Health Organization (WHO). Conventional Alzheimer's treatments such as chemotherapy, surgery, and radiotherapy are not very effective and are usually associated with several adverse effects. Therefore, it is necessary to find a new therapeutic approach that completely treats Alzheimer's disease without many side effects. In this research project, we report the synthesis and biological activities of some new thiazole-bearing sulfonamide analogs (1-21) as potent anti-Alzheimer's agents. Suitable characterization techniques were employed, and the density functional theory (DFT) computational approach, as well as in-silico molecular modeling, has been employed to assess the electronic properties and anti-Alzheimer's potency of the analogs. All analogs exhibited a varied degree of inhibitory potential, but analog 1 was found to have excellent potency (IC50 = 0.10 ± 0.05 µM for AChE) and (IC50 = 0.20 ± 0.050 µM for BuChE) as compared to the reference drug donepezil (IC50 = 2.16 ± 0.12 µM and 4.5 ± 0.11 µM). The structure-activity relationship was established, and it mainly depends upon the nature, position, number, and electron-donating/-withdrawing effects of the substituent/s on the phenyl rings.

A woman in her fifties with cirrhosis of the liver and postural dyspnoea. / En kvinne i 50-årene med levercirrhose og stillingsavhengig dyspné.

A woman in her fifties with advanced cirrhosis of the liver was admitted multiple times with recurrent pleural effusion and ascites. She was accepted for liver transplantation, at which time she developed postural dyspnoea and a drop in oxygen saturation.

Association of different blood groups in patients with Dengue fever and their relationship with the severity of the illness.

Objective: To determine the association of different blood groups in patients with Dengue fever and their relationship with the severity of the illness. Methods: A hospital-based descriptive study was conducted in the Dengue Isolation Ward of Lady Reading Hospital Peshawar from March 2020 to September 2020. Patients with Dengue fever were included in the study. The severity of the illness was categorized as "Dengue fever (DF)", "Dengue hemorrhagic fever (DHF)", and "Dengue shock syndrome (DSS)". The patients' blood groups were determined as A, B, AB, and O groups. All the data were recorded and analyzed using SPSS® version 23. Chi-square (χ2) and student t-test were applied, and a p-value of ≤0.05 was considered significant. Results: Out of 160 patients, 119(74.4%) were males; the patient's mean age was 38.09±15.68 SD, IQR=25 years. Greater proportion (28%) of the young men (up to 40 years) was affected compared to 9% young women. Fever (99%) and body aches (96%) were the most common presentation of DF, complicated by bleeding in 30.6% and shock in 9.4% of the patients. The majority (63.1%) of the patients had DF; 27.5% had DHF, and 9.4% had DSS. Sixty three (39.4%) patients had blood Group-B and 5.6% had Group-AB (p=0.97). The proportion of patients with different blood groups and the type/severity of the DF were almost identical except the fact that none of the patient with group AB had DSS. There was significant gender difference of hemoglobin (p=0.008, 95%CI=0.439, 2.844), hematocrit (p=0.012, 95%CI=0.00974, 0.07946); and Alanine Aminotransferase levels (p=0.002, 95%CI=-332.032, -72.233). Conclusion: Patients with blood Group-B were more frequent and AB was least commonly affected by the Dengue-virus infections. However, no association was found between a particular blood group and disease severity. Greater proportions of the younger men had Dengue infections.

Exploring the Antibiotic Production Potential of Heterotrophic Bacterial Communities Isolated from the Marine Sponges Crateromorpha meyeri, Pseudaxinella reticulata, Farrea similaris, and Caulophacus arcticus through Synergistic Metabolomic and Genomic Analyses.

The discovery of novel secondary metabolites is actively being pursued in new ecosystems. Sponge-associated bacteria have been in the limelight in recent years on account of their ability to produce bioactive compounds. In this study, heterotrophic bacteria associated with four sponge species were isolated, taxonomically identified, and subjected to screening for the production of bioactive entities against a panel of nine microorganisms, including Gram-positive and negative bacteria, as well as yeast and fungi. Of the 105 isolated strains, 66% were represented by Proteobacteria, 16% by Bacteriodetes, 7% by Actinobacteria, and 11% by Firmicutes. Bioactivity screening revealed that 40% of the total isolated strains showed antimicrobial activity against one or more of the target microorganisms tested. Further, active extracts from selective species were narrowed down by bioassay-guided fractionation and subsequently identified by HR-ESI-MS analyses to locate the active peaks. Presumably responsible compounds for the observed bioactivities were identified as pentadecenoic acid, oleic acid, and palmitoleic acid. One isolate, Qipengyuania pacifica NZ-96T, based on 16S rRNA novelty, was subjected to comparative metabolic reconstruction analysis with its closest phylogenetic neighbors, revealing 79 unique functional roles in the novel isolate. In addition, genome mining of Qipengyuania pacifica NZ-96T revealed three biosynthetic gene clusters responsible for the biosynthesis of terpene, beta lactone, lasso peptide, and hserlactone secondary metabolites. Our results demonstrate the ability to target the sponge microbiome as a potential source of novel microbial life with biotechnological potential.

The first molecular identification and phylogenetic analysis of tick-borne pathogens in captive wild animals from Lohi Bher zoo, Pakistan.

Tick-borne pathogens are causing severe diseases in livestock, wild animals, and humans. Wild animals play a crucial role in tick-borne pathogens' transmission life cycle by serving as reservoir hosts or intermediate hosts, posing a continuous risk for domestic animals and humans. The presence of tick-borne pathogens is often ignored in wild animals kept in zoos, which is a public health concern. In the present study, we investigated these pathogens in tick-infested captive wild animals at the Lohi Bher zoo, Pakistan. Blood samples were collected from 22 animals, which include urials (4) (Ovis aries vignei), blackbucks (3) (Antilope cervicapra), fallow deer (1) (Dama dama), hog deer (6) (Axis porcinus), chinkaras (4) (Gazella bennettii), white tiger (2) (Panthera tigris tigris), a giraffe (Giraffa camelopardalis), and African lions (2) (Panthera leo). The samples were screened for Piroplasm and Anaplasma spp. by polymerase chain reaction targeting different gene loci. We detected three Theileria spp. and one Anaplasma sp. from the investigated captive wild animals. The Theileria sp. dama gazelle was detected from chinkara, Theileria sp. NG-2012b from chinkara and giraffe and T. parva from African lion, and Anaplasma bovis was identified in a giraffe. Moreover, Theileria sp. and Anaplasma sp. coinfection was detected in one giraffe. Overall, this study shows that Theileria spp. and Anaplasma spp. are circulating in captive wild animals, which can play an important role in their spread. Further studies are required to monitor tick-borne pathogens in zoo animals and their potential to spread from exotic wild captive animals to local wild and domestic.

A Multiband Shared Aperture MIMO Antenna for Millimeter-Wave and Sub-6GHz 5G Applications.

A shared aperture 2-element multiple-input-multiple-output (MIMO) antenna design for 5G standards is presented in this study, one which uses the same radiating structure to cover both the sub-6GHz and millimeter-wave (millimeter-wave) bands. The proposed antenna comprises four concentric pentagonal slots that are uniformly separated from one another. For the sub-6GHz band, the antenna is excited by a single open-end microstrip transmission-line, while a 1 × 8 power divider (PD) connected via a T-junction structure excites the millimeter-wave band. Both the sub-6GHz and mm-wave antennas operate in a MIMO configuration. The proposed antenna design was fabricated on a 120 × 60 mm2 substrate with an edge-to-edge distance of 49 mm. The proposed sub-6GHz antenna covers the following frequency bands: 4-4.5 GHz, 3.1-3.8 GHz, 2.48-2.9 GHz, 1.82-2.14 GHz, and 1.4-1.58 GHz, while the millimeter-wave antenna operates at 28 GHz with at least 500 MHz of bandwidth. A complete antenna analysis is provided via a step-by-step design procedure, an equivalent circuit diagram showing the operation of the shared aperture antenna, and current density analysis at both millimeter-wave and sub-6GHz bands. The proposed antenna design is also characterized in terms of MIMO performance metrics with a good MIMO operation with maximum envelop correlation coefficient value of 0.113. The maximum measured gain and efficiency values obtained were 91% and 8.5 dBi over the entire band of operation. The antenna is backward compatible with 4G bands and also encompasses the sub-6GHz and 28 GHz bands for future 5G wireless communcation systems.

Synthesis of New Triazole-Based Thiosemicarbazone Derivatives as Anti-Alzheimer's Disease Candidates: Evidence-Based In Vitro Study.

Triazole-based thiosemicarbazone derivatives (6a-u) were synthesized then characterized by spectroscopic techniques, such as 1HNMR and 13CNMR and HRMS (ESI). Newly synthesized derivatives were screened in vitro for inhibitory activity against acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) enzymes. All derivatives (except 6c and 6d, which were found to be completely inactive) demonstrated moderate to good inhibitory effects ranging from 0.10 ± 0.050 to 12.20 ± 0.30 µM (for AChE) and 0.20 ± 0.10 to 14.10 ± 0.40 µM (for BuChE). The analogue 6i (IC50 = 0.10 ± 0.050 for AChE and IC50 = 0.20 ± 0.050 µM for BuChE), which had di-substitutions (2-nitro, 3-hydroxy groups) at ring B and tri-substitutions (2-nitro, 4,5-dichloro groups) at ring C, and analogue 6b (IC50 = 0.20 ± 0.10 µM for AChE and IC50 = 0.30 ± 0.10 µM for BuChE), which had di-Cl at 4,5, -NO2 groups at 2-position of phenyl ring B and hydroxy group at ortho-position of phenyl ring C, emerged as the most potent inhibitors of both targeted enzymes (AChE and BuChE) among the current series. A structure-activity relationship (SAR) was developed based on nature, position, number, electron donating/withdrawing effects of substitution/s on phenyl rings. Molecular docking studies were used to describe binding interactions of the most active inhibitors with active sites of AChE and BuChE.

Pregnancy related complications due to obesity and gestational diabetes mellitus among women in Saudi Arabia.

Gestational Diabetes mellitus (GDM) is one of the major maternal health problems in Middle East countries. In Saudi Arabia, the prevalence rates of GDM fall in the range of 16.2% to 24.2%. The study determined the antenatal complications and adverse pregnancy outcomes associated with GDM among a sample of Obese/GDM and Non-Obese/GDM women. A record based retrospective study was conducted including females who received obstetric care in a tertiary care hospital in Ha'il city of Saudi Arabia from December 2020 to June 2021. We gathered data from the medical records of 376 pregnant females who were registered and delivered at Maternity and Children Hospital (MCH). Multinomial regression analysis was applied to determine independent association of GDM and Obesity with pre-postnatal health outcomes. Out of 376 pregnant women 29.2% were identified as (Non-Obese/Non-GDM); 37.1% of women as having both conditions (GDM/Obesity); 19.2% as (Non-Obese/GDM) and 14.1% as (Obese/Non-GDM). The proportion of underweight and overweight babies were high in women with both conditions (Obese/GDM). Findings from our regression analysis demonstrated that Non-Obese/GDM women were 2.7 times more likely to have high child birthweight (p <0.001) when compared to Non-Obese/Non-GDM. Obese/GDM women were more likely to have low Appearance, Pulse, Grimace, Activity, and Respiration (APGAR) scores (p <0.001) and increase neonatal intensive care unit (NICU) admissions (p<0.01). Healthcare policy makers and professionals should revisit gaps in existing obstetrical care to prevent adverse impact on women and newborn health. Non-Obese women at risk of GDM should also be given due attention for early screening, timely diagnosis, and appropriate pre-postnatal care.

Macrosomia predictors and pregnancy outcomes in Gestational Diabetes patients: An observational study from Ha'il, Saudi Arabia.

Objectives: To determine the prevalence, risk factors for macrosomia and pregnancy outcome in women with gestational diabetes (GDM). Methods: In this prospective observational study, we included the data of 161 pregnant females diagnosed with GDM. The study was conducted from December 1st, 2020 to June 30, 2021, at the Maternity and Children Hospital (MCH) of Hail, Saudi Arabia. The data regarding risk factors of macrosomia was obtained from each patient. The patients were followed till the delivery of the baby. The data regarding the prevalence of fetal macrosomia and its associated outcomes was noted. Results: The prevalence of fetal macrosomia was 19.8%. Maternal obesity (OR 4.87), poorly controlled diabetes (OR 3.3), previous history of good-sized baby (OR 2.30), previous history of congenital abnormalities (OR 7.2) were the significant risk factors of fetal macrosomia. The prevalence of maternal and fetal complications was high among pregnancies complicated by fetal macrosomia. The prevalence of fetal macrosomia and other fetal complications was high in poorly controlled GDM patients in comparison to optimal control GDM patients. Conclusion: Fetal macrosomia is a common complication among GDM patients. Maternal obesity and poorly controlled diabetes are the common modifiable maternal factors contributing to macrosomia.

Evaluation and docking of indole sulfonamide as a potent inhibitor of α-glucosidase enzyme in streptozotocin -induced diabetic albino wistar rats.

We have synthesized new hybrid class of indole bearing sulfonamide scaffolds (1-17) as α-glucosidase inhibitors. All scaffolds were found to be active except scaffold 17 and exhibited IC50 values ranging from 1.60 to 51.20 µM in comparison with standard acarbose (IC50 = 42.45 µM). Among the synthesized hybrid class scaffolds 16 was the most potent analogue with IC50 value 1.60 µM, showing many folds better potency as compared to standard acarbose. Whereas, synthesized scaffolds 1-15 showed good α-glucosidase inhibitory potential. Based on α-glucosidase inhibitory effect, Scaffold 16 was chosen due to highest activity in vitro for further evaluation of antidiabetic activity in Streptozotocin induced diabetic rats. The Scaffold 16 exhibited significant antidiabetic activity. All analogues were characterized through 1H, 13CNMR and HR MS. Structure-activity relationship of synthesized analogues was established and confirmed through molecular docking study.

Synthesis of indole-based-thiadiazole derivatives as a potent inhibitor of α-glucosidase enzyme along with in silico study.

A series of nineteen (1-19) indole-based-thiadiazole derivatives were synthesized, characterized by 1HNMR, 13C NMR, MS, and screened for α-glucosidase inhibition. All analogs showed varied α-glucosidase inhibitory potential with IC50 value ranged between 0.95 ± 0.05 to 13.60 ± 0.30 µM, when compared with the standard acarbose (IC50 = 1.70 ± 0.10). Analogs 17, 2, 1, 9, 7, 3, 15, 10, 16, and 14 with IC50 values 0.95 ± 0.05, 1.10 ± 0.10, 1.30 ± 0.10, 1.60 ± 0.10, 2.30 ± 0.10, 2.30 ± 0.10, 2.80 ± 0.10, 4.10 ± 0.20 and 4.80 ± 0.20 µM respectively showed highest α-glucosidase inhibition. All other analogs also exhibit excellent inhibitory potential. Structure activity relationships have been established for all compounds primarily based on substitution pattern on the phenyl ring. Through molecular docking study, binding interactions of the most active compounds were confirmed. We further studied the kinetics study of analogs 1, 2, 9 and 17 and found that they are Non-competitive inhibitors.

Synthesis, in vitro antiurease, in vivo antinematodal activity of quinoline analogs and their in-silico study.

Synthesis of quinoline analogs and their urease inhibitory activities with reference to the standard drug, thiourea (IC50 = 21.86 ± 0.40 µM) are presented in this study. The inhibitory activity range is (IC50 = 0.60 ± 0.01 to 24.10 ± 0.70 µM) which displayed that it is most potent class of urease inhibitor. Analog 1-9, and 11-13 emerged with many times greater antiurease potential than thiourea, in which analog 1, 2, 3, 4, 8, 9, and 11 (IC50 = 3.50 ± 0.10, 7.20 ± 0.20, 1.30 ± 0.10, 2.30 ± 0.10, 0.60 ± 0.01, 1.05 ± 0.10 and 2.60 ± 0.10 µM respectively) were appeared the most potent ones among the series. In this context, most potent analogs such as 1, 3, 4, 8, and 9 were further subjected for their in vitro antinematodal study against C. elegans to examine its cytotoxicity under positive control of standard drug, Levamisole. Consequently, the cytotoxicity profile displayed that analogs 3, 8, and 9 were found with minimum cytotoxic outline at higher concentration (500 µg/mL). All analogs were characterized through 1H NMR, 13C NMR and HR-EIMS. The protein-ligand binding interaction for most potent analogs was confirmed via molecular docking study.

Mitigating Wireless Channel Impairments in Seismic Data Transmission Using Deep Neural Networks.

The traditional cable-based geophone network is an inefficient way of seismic data transmission owing to the related cost and weight. The future of oil and gas exploration technology demands large-scale seismic acquisition, versatility, flexibility, scalability, and automation. On the one hand, a typical seismic survey can pile up a massive amount of raw seismic data per day. On the other hand, the need for wireless seismic data transmission remains immense. Moving from pre-wired to wireless geophones faces major challenges given the enormous amount of data that needs to be transmitted from geophones to the on-site data collection center. The most important factor that has been ignored in the previous studies for the realization of wireless seismic data transmission is wireless channel effects. While transmitting the seismic data wirelessly, impairments like interference, multi-path fading, and channel noise need to be considered. Therefore, in this work, a novel amalgamation of blind channel identification and deep neural networks is proposed. As a geophone already is responsible for transmitting a tremendous amount of data under tight timing constraints, the proposed setup eschews sending any additional training signals for the purpose of mitigating the channel effects. Note that the deep neural network is trained only on synthetic seismic data without the need to use real data in the training process. Experiments show that the proposed method gives promising results when applied to the real/field data set.

Fatigue Crack Monitoring of T-Type Joints in Steel Offshore Oil and Gas Jacket Platform.

Several approaches have been used in the past to predict fatigue crack growth rates in T-joints of the offshore structures, but there are relatively few cases of applying structural health monitoring during the non-destructive testing of jacket platforms. This paper presents an experimental method based on the sensing of the piezoelectric sensors and finite element analysis method for studying the fatigue cracks in the offshore steel jacket structure. Three types of joints are selected in the current research work: T-type plate, T-type tube-plate, and T-type tube joints. The finite element analysis model established in the current study computes and analyzes the high stress and high strain regions in the T-type joints. The fatigue damage in the T-type joints was successfully detected by utilizing both the finite element analysis and experimental methods. The results showed that fatigue cracks of the three types of joints are prone to appear at the weld toe and spread in the welding direction. The fatigue damage location of T-type plate and T-type tube-plate joints is more concentrated in the upper weld toe area, and the fatigue damage location of the T-type tube joint is closer to the lower weld toe area.

Wheat Yellow Rust Disease Infection Type Classification Using Texture Features.

Wheat is a staple crop of Pakistan that covers almost 40% of the cultivated land and contributes almost 3% in the overall Gross Domestic Product (GDP) of Pakistan. However, due to increasing seasonal variation, it was observed that wheat is majorly affected by rust disease, particularly in rain-fed areas. Rust is considered the most harmful fungal disease for wheat, which can cause reductions of 20-30% in wheat yield. Its capability to spread rapidly over time has made its management most challenging, becoming a major threat to food security. In order to counter this threat, precise detection of wheat rust and its infection types is important for minimizing yield losses. For this purpose, we have proposed a framework for classifying wheat yellow rust infection types using machine learning techniques. First, an image dataset of different yellow rust infections was collected using mobile cameras. Six Gray Level Co-occurrence Matrix (GLCM) texture features and four Local Binary Patterns (LBP) texture features were extracted from grayscale images of the collected dataset. In order to classify wheat yellow rust disease into its three classes (healthy, resistant, and susceptible), Decision Tree, Random Forest, Light Gradient Boosting Machine (LightGBM), Extreme Gradient Boosting (XGBoost), and CatBoost were used with (i) GLCM, (ii) LBP, and (iii) combined GLCM-LBP texture features. The results indicate that CatBoost outperformed on GLCM texture features with an accuracy of 92.30%. This accuracy can be further improved by scaling up the dataset and applying deep learning models. The development of the proposed study could be useful for the agricultural community for the early detection of wheat yellow rust infection and assist in taking remedial measures to contain crop yield.

Synthesis of symmetrical bis-Schiff base-disulfide hybrids as highly effective anti-leishmanial agents.

Leishmaniasis has affected a wider part of population around the globe. Most often, the existing regiments to battle against leishmaniasis are inadequate and limited. In our ongoing efforts to develop new leishmanicidal agents, we have synthesized a series of novel and symmetrical bis-Schiff base-disulfide hybrids 1-27. Intermediate disulfide was synthesized from corresponding 2-aminothiol followed by reacting the coupled adduct with various aromatic aldehydes. All these compounds showed outstanding inhibition when compared with standard (Table 1). Out of twenty seven analogues, twenty two analogues i.e. 1-5, 7-13, 17-21, 23-27 analogues showed excellent inhibitory potential with EC50 values ranging from 0.010 ± 0.00 to 0.096 ± 0.01 µM while five compounds i.e. 6, 14-16, and 22 showed good inhibitory potential with EC50 values ranging from 0.10 ± 0.00 to 0.137 ± 0.01 µM when compared with the standard Amphotericin B. Structure-activity relationship has been established while molecular docking studies were performed to pin the binding interaction of active molecules. This study will help to develop new antileishmanial lead compounds.

Synthesis of indole based acetohydrazide analogs: Their in vitro and in silico thymidine phosphorylase studies.

In this study, a series of indole based acetohydrazide derivatives (1-22) were synthesized and characterized by 13C NMR, 1H NMR and HREI-MS. The resulted derivatives were tested for thymidine phosphorylase inhibitory potential. These derivatives inhibited thymidine phosphorylase at different concentration ranging from 1.10 ± 0.10 to 41.10 ± 1.10 µM when compared with the standard 7-Deazaxanthine (IC50 value 38.68 ± 1.12 µM). The compound 8 having OH group at 2, 4 and 6 position was found the most potent among the series with IC50 1.10 ± 0.10 µM. The structure activity relationships (SAR) has been established for all compounds keeping in the view the role of substitution and the effect of functional group which significantly affect thymidine phosphorylase activity. The nature of binding interactions of the most potent compounds and active sites of the enzymes was confirmed through molecular docking study.

Efficacy of open reduction and internal fixation in achieving bony union of comminuted mandibular fractures caused by civilian gunshot injuries.

INTRODUCTION: Comminuted fractures of the mandible caused by gunshot injuries were traditionally treated with closed reduction using maxillo-mandibular fixation (MMF).2,3 Open reduction and internal fixation (ORIF) has become a valuable treatment modality in the management of comminuted mandibular fractures due to low rate of complications and predictable healing 4, 5. OBJECTIVE: To compare the efficacy of ORIF compared with MMF in achieving bony union of comminuted mandibular fractures in gunshot injury patients. METHOD: ology: Randomized controlled trial conducted at the department of Oral & Maxillofacial Surgery, Abbasi Shaheed Hospital for a period of 3 years; total of 40 patients divided equally into two groups. Group A were treated with ORIF and group B were treated with MMF. Callus formation radiographically was confirmed by 8th week post operatively. Data was collected using proforma, entered on a statistical software SPSS version 20. Frequency percentages were computed for age and gender. Chi square and Fisher's exact tests were applied. P value ≤ 0.05 considered significant. RESULT: A total of 40 patients of gunshot injuries were included in this study. 37 (92.5%) were males and 3 (7.5%) were Females with mean age of 36.35 ± 12.9 years SD. 19 (47.5%) patients showed callus formation, whereas, 21 (52.5%) did not. Out of 19 patients, 14 (70%) belonged to group A, and 5 (25%) from group B. The final healing considered by 8th week was in 16 (80%) of ORIF group A, and 8 (40%) group B (MMF) after calculating the clinical and radiographic evidences. CONCLUSION: Comparative clinical trials have proven that ORIF is superior to MMF in the management of comminuted mandibular fractures. Early primary repair and internal fixation provides predictable and cost effective results.

Precision Agriculture Techniques and Practices: From Considerations to Applications.

Internet of Things (IoT)-based automation of agricultural events can change the agriculture sector from being static and manual to dynamic and smart, leading to enhanced production with reduced human efforts. Precision Agriculture (PA) along with Wireless Sensor Network (WSN) are the main drivers of automation in the agriculture domain. PA uses specific sensors and software to ensure that the crops receive exactly what they need to optimize productivity and sustainability. PA includes retrieving real data about the conditions of soil, crops and weather from the sensors deployed in the fields. High-resolution images of crops are obtained from satellite or air-borne platforms (manned or unmanned), which are further processed to extract information used to provide future decisions. In this paper, a review of near and remote sensor networks in the agriculture domain is presented along with several considerations and challenges. This survey includes wireless communication technologies, sensors, and wireless nodes used to assess the environmental behaviour, the platforms used to obtain spectral images of crops, the common vegetation indices used to analyse spectral images and applications of WSN in agriculture. As a proof of concept, we present a case study showing how WSN-based PA system can be implemented. We propose an IoT-based smart solution for crop health monitoring, which is comprised of two modules. The first module is a wireless sensor network-based system to monitor real-time crop health status. The second module uses a low altitude remote sensing platform to obtain multi-spectral imagery, which is further processed to classify healthy and unhealthy crops. We also highlight the results obtained using a case study and list the challenges and future directions based on our work.