IoT Based Smart Assist System to Monitor Entertainment Spots Occupancy and COVID 19 Screening During the Pandemic.

The greatest threat to the word in recent days is the spread of COVID 19 virus throughout the world. To tackle this problem government of India has implemented various restrictions to be followed to stop the spread of the COVID 19 virus. But most of the time general public forget their responsibilities and don't follow these restrictions, especially in situations like when their favourite hero's movie releases in the theatre, and in spending time in hotels, malls and in other entertainment places in spite of governments occupancy restrictions in those places. In order to address this problem we propose an IoT based Smart System for monitoring the occupancy in such entertainment spots and screen the public entry if they dint follow the protocols such as if they dint wear mask or if they have body temperature. This proposed system is implemented on a Raspberry Pi 3B+ processor which runs on a Broadcom processor. For monitoring the occupancy and screen the visitors for mask, we use a Passive Infrared Sensors and Pi camera to count the person entering into the premises. And we use a MLX90614 Infrared temperature sensor for screening the public entry with high temperature. The complete system is implemented using python programming and the details will be uploaded to cloud, authorities can monitor this from a remote place so that the spread of COVID 19 can be restricted in pubic entertainment spots.

Banana Plant Disease Classification Using Hybrid Convolutional Neural Network.

Banana cultivation is one of the main agricultural elements in India, while the common problem of cultivation is that the crop has been influenced by several diseases, while the pest indications have been needed for discovering the infections initially for avoiding the financial loss to the farmers. This problem will affect the entire banana productivity and directly affects the economy of the country. A hybrid convolution neural network (CNN) enabled banana disease detection, and the classification is proposed to overcome these issues guide the farmers through enabling fertilizers that have to be utilized for avoiding the disease in the initial stages, and the proposed technique shows 99% of accuracy that is compared with the related deep learning techniques.

Fuzzy Guided Autonomous Nursing Robot through Wireless Beacon Network.

Robotics is one of the most emerging technologies today, and are used in a variety of applications, ranging from complex rocket technology to monitoring of crops in agriculture. Robots can be exceptionally useful in a smart hospital environment provided that they are equipped with improved vision capabilities for detection and avoidance of obstacles present in their path, thus allowing robots to perform their tasks without any disturbance. In the particular case of Autonomous Nursing Robots, major essential issues are effective robot path planning for the delivery of medicines to patients, measuring the patient body parameters through sensors, interacting with and informing the patient, by means of voice-based modules, about the doctors visiting schedule, his/her body parameter details, etc. This paper presents an approach of a complete Autonomous Nursing Robot which supports all the aforementioned tasks. In this paper, we present a new Autonomous Nursing Robot system capable of operating in a smart hospital environment area. The objective of the system is to identify the patient room, perform robot path planning for the delivery of medicines to a patient, and measure the patient body parameters, through a wireless BLE (Bluetooth Low Energy) beacon receiver and the BLE beacon transmitter at the respective patient rooms. Assuming that a wireless beacon is kept at the patient room, the robot follows the beacon's signal, identifies the respective room and delivers the needed medicine to the patient. A new fuzzy controller system which consists of three ultrasonic sensors and one camera is developed to detect the optimal robot path and to avoid the robot collision with stable and moving obstacles. The fuzzy controller effectively detects obstacles in the robot's vicinity and makes proper decisions for avoiding them. The navigation of the robot is implemented on a BLE tag module by using the AOA (Angle of Arrival) method. The robot uses sensors to measure the patient body parameters and updates these data to the hospital patient database system in a private cloud mode. It also makes uses of a Google assistant to interact with the patients. The robotic system was implemented on the Raspberry Pi using Matlab 2018b. The system performance was evaluated on a PC with an Intel Core i5 processor, while the solar power was used to power the system. Several sensors, namely HC-SR04 ultrasonic sensor, Logitech HD 720p image sensor, a temperature sensor and a heart rate sensor are used together with a camera to generate datasets for testing the proposed system. In particular, the system was tested on operations taking place in the context of a private hospital in Tirunelveli, Tamilnadu, India. A detailed comparison is performed, through some performance metrics, such as Correlation, Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE), against the related works of Deepu et al., Huh and Seo, Chinmayi et al., Alli et al., Xu, Ran et al., and Lee et al. The experimental system validation showed that the fuzzy controller achieves very high accuracy in obstacle detection and avoidance, with a very low computational time for taking directional decisions. Moreover, the experimental results demonstrated that the robotic system achieves superior accuracy in detecting/avoiding obstacles compared to other systems of similar purposes presented in the related works.

Novel framework of GIS based automated monitoring process on environmental biodegradability and risk analysis using Internet of Things.

A proper method on real-time monitoring of organic biomass degradation and its evaluation for safeguarding the ecosystem is the need of the hour. The work process designed in this study is to demarcate the anaerobic digestion potential using kinetic modelling and web GIS application methods. Wastewater source that causes pollution are identified through satellite maps such as solid earth, drain system, surface of earth structure, land filling and land use. The grabbed data are utilized for identifying the concentration of sludge availability. Based on literature resource multi influencing factor techniques are introduced along with overlay method to differentiate digestion potential of sludge source. This study optimizes the biodegradation potential of domestic sewage at different sludge concentrations in a pilot model operated with the samples identified through topographical drainage survey. The materialization of devices is using the Internet of Things (IoTs), that is pragmatic to be the promising tendency. Kinetic study, methanogenic assay test are performed with three different cation binding agents to find its solubilization potential and methane evolution, which is further subjected to digestion potential in anaerobic conditions for possible application in the field of environmental science. Risk analysis reveals that land filling method will have highest impact on maintaining sustainable environment. The results outcome on natural biodegradation may be used for individual house hold wastewater management for the locality.

Deep learning based genome analysis and NGS-RNA LL identification with a novel hybrid model.

The conventional image segmentation techniques have a lot of issues with highest computational cost and low level accuracy for medical image diagnosis and genome analysis. The deep learning based optimization models utilize to predict the liver cancer with RNA genome using CT images and the prediction of genome classification with NGS is a higher probable in recent medical disease classification. This paper proposes a hybrid deep learning technique constructs with SegNet, MultiResUNet, and Krill Herd optimization (KHO) algorithm to perform the extraction of the liver lesions and RNA sequencing that the optimization techniques used into the deep learning method. The proposed technique implements the SegNet for segregating the liver with genome from the CT scan; the MultiResUNet is constructed to perform the extractions of liver lesions. The KHO algorithm is combined with the deep learning approaches for tuning the hyper parameters to every Convolutional neural network model and enhances the segmentation process which may elaborately identifies the sequence that causes the liver classification disease. The proposed technique is compared with the related techniques on liver lesion classification (LL) for NGS in genome. The performance results show that the proposed technique is better to other algorithms on various performance metrics.

ITFDS: Channel-Aware Integrated Time and Frequency-Based Downlink LTE Scheduling in MANET.

One of the crucial problems in Industry 4.0 is how to strengthen the performance of mobile communication within mobile ad-hoc networks (MANETs) and mobile computational grids (MCGs). In communication, Industry 4.0 needs dynamic network connectivity with higher amounts of speed and bandwidth. In order to support multiple users for video calling or conferencing with high-speed transmission rates and low packet loss, 4G technology was introduced by the 3G Partnership Program (3GPP). 4G LTE is a type of 4G technology in which LTE stands for Long Term Evolution, followed to achieve 4G speeds. 4G LTE supports multiple users for downlink with higher-order modulation up to 64 quadrature amplitude modulation (QAM). With wide coverage, high reliability and large capacity, LTE networks are widely used in Industry 4.0. However, there are many kinds of equipment with different quality of service (QoS) requirements. In the existing LTE scheduling methods, the scheduler in frequency domain packet scheduling exploits the spatial, frequency, and multi-user diversity to achieve larger MIMO for the required QoS level. On the contrary, time-frequency LTE scheduling pays attention to temporal and utility fairness. It is desirable to have a new solution that combines both the time and frequency domains for real-time applications with fairness among users. In this paper, we propose a channel-aware Integrated Time and Frequency-based Downlink LTE Scheduling (ITFDS) algorithm, which is suitable for both real-time and non-real-time applications. Firstly, it calculates the channel capacity and quality using the channel quality indicator (CQI). Additionally, data broadcasting is maintained by using the dynamic class-based establishment (DCE). In the time domain, we calculate the queue length before transmitting the next packets. In the frequency domain, we use the largest weight delay first (LWDF) scheduling algorithm to allocate resources to all users. All the allocations would be taken placed in the same transmission time interval (TTI). The new method is compared against the largest weighted delay first (LWDF), proportional fair (PF), maximum throughput (MT), and exponential/proportional fair (EXP/PF) methods. Experimental results show that the performance improves by around 12% compared with those other algorithms.

Design a prototype for automated patient diagnosis in wireless sensor networks.

It is indeed necessary to design of an elderly support mobile healthcare and monitoring system on wireless sensor network (WSN) for dynamic monitoring. It comes from the need for maintenance of healthcare among patients and elderly people that leads to the demand on change in traditional monitoring approaches among chronic disease patients and alert on acute events. In this paper, we propose a new automated patient diagnosis called automated patient diagnosis (AUPA) using ATmega microcontrollers over environmental sensors. AUPA monitors and aggregates data from patients through network connected over web server and mobile network. The scheme supports variable data management and route establishment. Data transfer is established using adaptive route discovery and management approaches. AUPA supports minimizing packet loss and delay, handling erroneous data, and providing optimized decision-making for healthcare support. The performance of AUPA's QoS approach is tested using a set of health-related sensors which gather the patient's data over variable period of time and send from a source to destination AUPA node. Experimental results show that AUPA outperforms the existing schemes, namely SPIN and LEACH, with minimal signal loss rate and a better neighborhood node selection and link selection. It diminishes the jitter compared to the related algorithms. Graphical abstract Stack architecture of AUPA.

Energy-Aware Multipath Routing Scheme Based on Particle Swarm Optimization in Mobile Ad Hoc Networks.

Mobile ad hoc network (MANET) is a collection of autonomous mobile nodes forming an ad hoc network without fixed infrastructure. Dynamic topology property of MANET may degrade the performance of the network. However, multipath selection is a great challenging task to improve the network lifetime. We proposed an energy-aware multipath routing scheme based on particle swarm optimization (EMPSO) that uses continuous time recurrent neural network (CTRNN) to solve optimization problems. CTRNN finds the optimal loop-free paths to solve link disjoint paths in a MANET. The CTRNN is used as an optimum path selection technique that produces a set of optimal paths between source and destination. In CTRNN, particle swarm optimization (PSO) method is primly used for training the RNN. The proposed scheme uses the reliability measures such as transmission cost, energy factor, and the optimal traffic ratio between source and destination to increase routing performance. In this scheme, optimal loop-free paths can be found using PSO to seek better link quality nodes in route discovery phase. PSO optimizes a problem by iteratively trying to get a better solution with regard to a measure of quality. The proposed scheme discovers multiple loop-free paths by using PSO technique.

Impaired erythropoiesis after haemorrhagic shock in mice is associated with erythroid progenitor apoptosis in vivo.

OBJECTIVE: Multiply traumatised patients often suffer from blood loss and from subsequent therapy-resistant anaemia, possibly mediated by apoptosis, necrosis, or humoral factors. Therefore, the underlying mechanisms were investigated in bone marrow (BM) and peripheral blood in a murine resuscitated haemorrhagic shock (HS) model. METHODS: In healthy male mice, pressure-controlled HS was induced for 60 min. The BM was analysed for Annexin-V, 7-amino-actinomycin D, apoptotic enzymes (caspases-3/7, -8, and -9), expression of death receptors (CD120a, CD95), mitochondrial proteins (Bax, Bcl-2, Bcl-x), as well as erythropoietin (EPO) receptor (EPO-R). Blood cell count, peripheral EPO, and tumour necrosis factor-alpha response were additionally monitored. RESULTS: Twenty-four and 72 h after HS, EPO and EPO-R were strongly up-regulated in peripheral blood and BM, respectively. Decreasing numbers of erythroid progenitors in BM after HS correlated with significant apoptotic changes confirmed by increased caspases-3/7, -8, -9 activity in total BM, death receptor CD95 and CD120a expression on erythroid progenitors, and down-regulated mitochondrial Bcl-2 expression in total BM. Erythroid progenitors in peripheral blood were found to be increased after 72 h. CONCLUSION: Despite the massive EPO response and up-regulation of EPO-R, BM erythroblasts (EBs) decreased. This could be due to deficient maturation of erythroid progenitors. Furthermore, the increased intrinsic and extrinsic apoptosis activation suggests programmed death of erythroid progenitors. We propose that both apoptosis and negatively regulated erythropoiesis contribute to BM dysfunction, while erythroid progenitor egress plays an additional role.

[Treatment options for problematic thoracic and lumbar osteoporotic fractures]. / Behandlungsmöglichkeiten bei thorakalen und lumbalen osteoporotischen Problemfrakturen.

Most osteoporotic sintering fractures are treated conservatively. However, persistent pain and consecutive spinal deformity may require certain cement-augmenting interventions. These procedures have proven their intermediate-term efficacy in pain reduction, prevention of progressive sintering and improvement of the overall quality of life in the majority of patients. In fractures with relevant spinal stenosis, persisting instability, gross deformity and trauma-associated osteoporotic fractures with or without neurological deficits, the therapeutic options may call for more extensive surgical procedures. In this regard, poor bone quality, age and respective comorbidities of the individual patient must be considered during preoperative planning and management. This article provides an overview of the diverse problem-solving strategies discussed in today's literature. It is generally acknowledged that any decision to perform surgery on an osteoporotic fracture is strongly case-dependent. Treating physicians must therefore master the complete therapeutic spectrum in order to meet this complex orthopedic challenge appropriately.

[Fatal complex fracture of the cervical spine in a patient with ankylosing spondylitis after a fall from a racing bicycle]. / Fatale komplexe HWS-Verletzung bei M. Bechterew nach Sturz mit dem Rennrad.

Patients with ankylosing spondylitis are endangered suffering from cervical spine fractures following falls caused by kyphosis, stiffness and osteoporotic bone quality of the spine. Risk sustaining neurological deficits is higher than average. We present a patient with ankylosing spondylitis, who was admitted to our hospital with a complex fracture pattern of the cervical spine after a fall from a racing cycle. In spite of early operative treatment the patient died in the follow up because of severe hypoxic brain damage. We discuss the area of conflict between the recommendation for sport activities in patients with ankylosing spondylitis and the resulting risks for the diseased spine.

Brown-Séquard syndrome caused by a high velocity gunshot injury: a case report.

STUDY DESIGN: Case report. OBJECTIVE: To present an unusual traumatic neurologic pathology caused by gunshot injury. SETTING: Spine unit of Department of Trauma and Orthopaedic Surgery, University Medical School, Charité - Campus Benjamin Franklin, Berlin, Germany. METHOD AND RESULT: A 35-year-old male sustained a gunshot injury from a machine gun. The projectile caused a fracture of the left pedicle of Th10. The spinal cord was indirectly damaged by cavitation that caused a Brown-Séquard syndrome (BSS). After a microscopically assisted posterior revision at T9/10 with removal of bullet and bone fragments from the spinal canal and debridement of the bullet cavity via extended fenestrectomy the patient gained his motor function back. The sensory deficit remained unchanged. CONCLUSION: BSS can be caused by bullet-related injury of the spinal canal with no direct damage of neural structures. The initial treatment is always based on the total injury pattern. Possible spinal cord injuries are only clarified after restitution of vital functions. Decompression of neural structures in shotgun injury is indicated in incomplete paraplegia, injury of intra-abdominal hollow organs or high velocity bullet wounds. Through debridement and decompression of neural structures and chronic damage caused by foreign body granulomas can be prevented. Secondary destabilization of the spine should be avoided.

[Rare pathological alterations of the upper cervical spine requiring surgical treatment]. / Seltene krankhafte Veränderungen der oberen Halswirbelsäule mit operativer Behandlungsindikation.

Because of its unique anatomy, specific diseases and lesions arise in the upper cervical spine, which differ widely from the rest of the spine. During the last two decades standardised diagnostic and therapeutic algorithms have been defined for most of the craniocervical pathologies often occurring in combination with an underlying disease requiring surgical intervention as well. On the other hand there are some very rare phathological alterations: about 20% of the patients suffering from neurofibromatosis type I develop spinal deformities. These are mostly found in the thoracic and lumbar spine (dystrophic/non-dystrophic type). In rare cases the dystrophic neurofibromatosis type I involves the upper cervical spine leading to bizarre deformities endangering the spinal cord. An aggressive, timely and combined operative therapy is necessary. Patients with Down syndrome should be investigated regularly for affections of the upper cervical spine. Though only in about 1% of all patients with Down syndrome do instabilities require surgical intervention, the upper cervical spine should be screened on a regular basis, since neurological changes due to the pathognomy of the underlying disease often remain undetected for a long time. The operative therapy of the instable os odontoideum in Down syndrome follows the general principles of this pathoanatomical variation. Even though the Klippel-Feil syndrome is generally not linked with neuropathological findings, rare associated deformities of the upper cervical spine should be excluded by proper diagnostic procedures.

Spinal extradural meningeal cyst with spinal stenosis.

STUDY DESIGN: Case report. OBJECTIVE: To present a rare pathology causing a common disease. SETTING: Spine unit of the orthopaedic surgery department of a university hospital in Berlin/Germany. CASE REPORT: A 39-year-old female with an intraspinal extradural arachnoid cyst of the lumbar spine presented with intermittent radiating lumbar pain. The magnetic resonance imaging (MRI) showed a dorsal spinal extradural arachnoid cyst at L3/4. After wide laminotomy L3, operative cyst resection and stabilisation at L3/4 by posterior lumbar interbody fusion (PLIF), major symptom relief occurred. CONCLUSION: Spinal extradural arachnoid cysts are a rare entity causing low back pain and intermittent radicular syndromes. They can be caused by arachnoid herniation through dural weak spots which are hereditary or occur after trauma. A ball-valve mechanism promotes growth. The main diagnostic tool for spinal extradural cysts is the MRI scan. Additionally, myelography is helpful to demonstrate fluid communication. Complete surgical removal of the cyst should be attempted to reduce risk of recurrence. If extensive decompression is needed for the surgical approach causing segmental instability, interbody fusion is recommended. The outcome depends on age, duration and degree of neurological damage.

Isolation of Newcastle disease virus and Salmonella typhimurium from the brain of double-crested cormorants (Phalacrocorax auritus).

Avian paramyxovirus type 1 (Newcastle disease virus) and Salmonella typhimurium were isolated from the brain and lung tissues of double-crested cormorants (Phalacrocorax auritus) from Lac Canard, Alberta, Canada. More than 100 birds died during this outbreak in 1999. Affected birds presented signs of central nervous system disease characterized by unilateral wing and leg paralysis. Other geographic locations in the provinces of Alberta and Saskatchewan have reported cases of cormorants suffering from diseases with signs compatible with Newcastle disease. The virus isolated in the 1999 outbreak was characterized as mesogenic. These findings suggest that other pathogens, like S. typhimurium, may influence the clinical presentation of disease caused by mesogenic strains of Newcastle disease virus in cormorants.

Incursion of epizootic hemorrhagic disease into the Okanagan Valley, British Columbia in 1999.

In September 1999, unusually high mortality rates in white-tailed deer and California bighorn sheep occurred in the southern Okanagan Valley. Necropsy and histopathologic findings were compatible with epizootic hemorrhagic disease (EHD); the presence of virus was not demonstrated. Subsequent serologic and polymerase chain reaction assays on sentinel cattle suggested an EHD virus incursion.

Assessment of the pathogenicity of an emu-origin influenza A H5 virus in ostriches (Struthio camelus).

Ostriches were inoculated with a laboratory-derived highly pathogenic avian influenza (HPAI) virus of emu origin, A/emu/TX/39924/93 (H5N2) clone c1B. The aim of this study was to evaluate the pathogenicity of this isolate for ostriches and assess the ability of routine virological and serological tests to detect infection. Avian influenza virus (AIV) was isolated from cloacal and tracheal swabs from 2 to 12 days post-infection. AIV was also isolated from brain, thymus, eyelid, spleen, ovary/testis, liver, air sac, proventriculum, duodenum, caecal tonsil, heart, pancreas, kidney, nasal gland and lung. Virus isolation was also possible from swabs of the luminal surfaces of the cloaca, jejunum, lower ileum, bursa of Fabricius, trachea and bone marrow. Birds seroconverted as early as 7 days post-infection. This study suggests that HPAI virus of emu origin replicates extensively in infected ostriches without causing significant clinical disease or mortality.

Velogenic Newcastle disease in imported caged birds.

Velogenic Newcastle disease was diagnosed in pet birds intended for importation into Canada. Virological and histopathological examination confirmed the presence of the disease. The group of birds was denied entry into Canada. Similar birds illegally imported are a potential source of velogenic Newcastle disease virus and are a threat to domestic poultry.