Endodontic management of three-rooted maxillary second premolar in a patient with bilateral occurrence of three roots in maxillary second premolars

The possibility of bilateral maxillary second premolars having three separate roots is quite low; however, it must be taken into account in clinical and radiographic evaluations during endodontic treatment. A correct clinical and radiographic diagnosis based on knowledge of root canal anatomy and critical interpretation of radiographs is necessary for a safer and successful endodontic treatment of these teeth. Failure of root canal treatment can occur due to missed roots/canals and often diagnosed when patient experiences continuous post-operative pain and discomfort. This case report describes the root canal treatment of a three-rooted maxillary second premolar in a patient with bilateral occurrence of three roots in maxillary second premolars

Morphological and topographic study of diaphyseal nutrient foramen of femur and its clinical implications in North Indian population

Background: Nutrient foramen of long bones defines the extent of bone vascularisation. Information regarding nutrient foramen is necessary to conserve circulation during orthopaedic and surgical procedures. The present study was conducted to examine the position, number and calibre of nutrient foramina in 100 dry femora belonging to North Indian population.Methods: The total length (TL) of each femur was measured by taking the measurement between the most proximal aspect of the head of the femur and the most distal aspect of the medial condyle. Number of nutrient foramina was determined by using a magnifying lens. Distance of nutrient foramen from upper end was measured. Direction and obliquity of nutrient foramina were noted. Position of nutrient foramina was determined in relation to length of femur and linea aspera. Caliber of nutrient foramen was measured using 18, 20, 22 and 24-gauge needles.Results: Length of femur on right side was 435.2 mm (Range 393-523 mm). Length of femur on left side was 437 mm (range 369-524). 78 (78%) femora had single nutrient foramen, 11 (11%) had double nutrient foramen and 11 (11%) had no nutrient foramen. All foramina were directed upwards. Maximum foramina were located in middle third of femur (84%) followed by upper third of femur (8%). Most common location was on the intermediate area between two lips of linea aspera (42%) followed closely by medial lip of linea aspera (36%).Conclusions: This study has provided additional data on the subject which will help in resection, surgical procedures and transplantation techniques by orthopedician in North Indian population

A rare occurrence of bilateral C-shaped roots in mandibular first and second premolars diagnosed with the aid of spiral computed tomography

The C-shaped canal system is an anatomical variation mostly seen in mandibular second molars, although it can also occur in maxillary and other mandibular molars. Such variation in the root canal anatomy is uncommon in mandibular first premolars and very rare in mandibular second premolars. The C-shaped canal is so named for the cross-sectional morphology of the root and root canal. The main anatomic feature of C-shaped canals is the presence of a fin or web connecting the individual root canals. Failure of the Hertwig's epithelial root sheath to fuse on the lingual or buccal root surface is the main cause of C-shaped roots, which always contain a C-shaped canal. This case report describes an unusual occurrence of C-shaped roots in mandibular first and second premolars bilaterally, diagnosed with the aid of spiral computed tomography

Comparative Assessment of Some Target Detection Algorithms for Hyperspectral Images

Target detection is of particular interest in hyperspectral image analysis as many unknown and subtle signals (spectral response) unresolved by multispectral sensors can be discovered in hyperspectral images. The detection of signals in the form of small objects and targets from hyperspectral sensors has a wide range of applications both civilian and military. It has been observed that a number of target detection algorithms are in vogue; each has its own advantages and disadvantages and assumptions. The selection of a particular algorithm may depend on the amount of information available as per the requirement of the algorithm, application area, the computational complexity etc. In the present study, three algorithms, namely, orthogonal subspace projection (OSP), constrained energy minimization (CEM) and a nonlinear version of OSP called kernel orthogonal subspace projection (KOSP), have been investigated for target detection from hyperspectral remote sensing data. The efficacy of algorithms has been examined over two different hyperspectral datasets which include a synthetic image and an AVIRIS image. The quality of target detection from these algorithms has been evaluated through visual interpretation as well as through receiver operating characteristic (ROC) curves. The performance of OSP algorithm has been found to be better than or comparable to CEM algorithm. However, KOSP out performs both the algorithms.Defence Science Journal, 2013, 63(1), pp.53-62, DOI:http://dx.doi.org/10.14429/dsj.63.376

Identifying Depressive Symptoms from Tweets: Figurative Language Enabled Multitask Learning Framework

Existing studies on using social media for deriving mental health status of users focus on the depression detection task. However, for case management and referral to psychiatrists, healthcare workers require practical and scalable depressive disorder screening and triage system. This study aims to design and evaluate a decision support system (DSS) to reliably determine the depressive triage level by capturing fine-grained depressive symptoms expressed in user tweets through the emulation of Patient Health Questionnaire-9 (PHQ-9) that is routinely used in clinical practice. The reliable detection of depressive symptoms from tweets is challenging because the 280-character limit on tweets incentivizes the use of creative artifacts in the utterances and figurative usage contributes to effective expression. We propose a novel BERT based robust multi-task learning framework to accurately identify the depressive symptoms using the auxiliary task of figurative usage detection. Specifically, our proposed novel task sharing mechanism, co-task aware attention, enables automatic selection of optimal information across the BERT layers and tasks by soft-sharing of parameters. Our results show that modeling figurative usage can demonstrably improve the model\u27s robustness and reliability for distinguishing the depression symptoms

Performance Evaluation of IoT Sensors in Urban Air Quality Monitoring: Insights from the IoT Sensor Performance Test

In this paper, we report on extensive experiments conducted to evaluate Internet of Things (IoT) sensor performance in monitoring urban air quality. As certified sensors showed a considerably reduced air quality measurement error of 4.3% compared to uncalibrated sensors at 8.5%, our results highlight the crucial function of sensor calibration. The performance of sensors was impacted by environmental factors; higher temperatures produced better accuracy (3.6%), while high humidity levels caused sensors to react more quickly (2.3 seconds). The average air quality index (AQI) recorded by inside sensors was 45, but outside sensors reported an AQI of 60. This indicates that the positioning of the sensors had a substantial influence on the air quality data. Additionally, the methods of data transmission were examined, and it was found that Wi-Fi-transmitting sensors had lower latency (0.6 seconds) and data loss (1.8%) than cellular-transmitting sensors. These results emphasize the significance of environmental factors, sensor placement strategy, sensor calibration, and suitable data transmission techniques in maximizing IoT sensor performance for urban air quality monitoring, ultimately leading to more accurate and dependable air quality assessment

Liposomal nanotheranostics for multimode targeted in vivo bioimaging and near‐infrared light mediated cancer therapy

Developing a nanotheranostic agent with better image resolution and high accumulation into solid tumor microenvironment is a challenging task. Herein, we established a light mediated phototriggered strategy for enhanced tumor accumulation of nanohybrids. A multifunctional liposome based nanotheranostics loaded with gold nanoparticles (AuNPs) and emissive graphene quantum dots (GQDs) were engineered named as NFGL. Further, doxorubicin hydrochloride was encapsulated in NFGL to exhibit phototriggered chemotherapy and functionalized with folic acid targeting ligands. Encapsulated agents showed imaging bimodality for in vivo tumor diagnosis due to their high contrast and emissive nature. Targeted NFGL nanohybrids demonstrated near infrared light (NIR, 750 nm) mediated tumor reduction because of generated heat and Reactive Oxygen Species (ROS). Moreover, NFGL nanohybrids exhibited remarkable ROS scavenging ability as compared to GQDs loaded liposomes validated by antitumor study. Hence, this approach and engineered system could open new direction for targeted imaging and cancer therapy.publishersversionpublishe