An Efficient Data Aggregation Algorithm for Cluster-based Sensor Network

Data aggregation in wireless sensor networks eliminates redundancy to improve bandwidth utilization and energy-efficiency of sensor nodes. One node, called the cluster leader, collects data from surrounding nodes and then sends the summarized information to upstream nodes. In this paper, we propose an algorithm to select a cluster leader that will perform data aggregation in a partially connected sensor network. The algorithm reduces the traffic flow inside the network by adaptively selecting the shortest route for packet routing to the cluster leader. We also describe a simulation framework for functional analysis of WSN applications taking our proposed algorithm as an exampl

A CUDA-based implementation of an improved SPH method on GPU

We present a CUDA-based parallel implementation on GPU architecture of a modified version of the Smoothed Particle Hydrodynamics (SPH) method. This modified formulation exploits a strategy based on the Taylor series expansion, which simultaneously improves the approximation of a function and its derivatives with respect to the standard formulation. The improvement in accuracy comes at the cost of an additional computational effort. The computational demand becomes increasingly crucial as problem size increases but can be addressed by employing fast summations in a parallel computational scheme. The experimental analysis showed that our parallel implementation significantly reduces the runtime, with speed-ups of up to 90,when compared to the CPU-based implementation

Atmospheric circulation patterns, cloud-to-ground lightning, and locally intense convective rainfall associated with debris flow initiation in the Dolomite Alps of northeastern Italy

The Dolomite Alps of northeastern Italy experience debris flows with great frequency during the summer months. An ample supply of unconsolidated material on steep slopes and a summer season climate regime characterized by recurrent thunderstorms combine to produce an abundance of these destructive hydro-geologic events. In the past, debris flow events have been studied primarily in the context of their geologic and geomorphic characteristics. The atmospheric contribution to these mass-wasting events has been limited to recording rainfall and developing intensity thresholds for debris mobilization. This study aims to expand the examination of atmospheric processes that preceded both locally intense convective rainfall (LICR) and debris flows in the Dolomite region. 500 hPa pressure level plots of geopotential heights were constructed for a period of 3 days prior to debris flow events to gain insight into the synoptic-scale processes which provide an environment conducive to LICR in the Dolomites. Cloud-to-ground (CG) lightning flash data recorded at the meso-scale were incorporated to assess the convective environment proximal to debris flow source regions. Twelve events were analyzed and from this analysis three common synoptic-scale circulation patterns were identified. Evaluation of CG flashes at smaller spatial and temporal scales illustrated that convective processes vary in their production of CF flashes (total number) and the spatial distribution of flashes can also be quite different between events over longer periods. During the 60 min interval immediately preceding debris flow a majority of cases exhibited spatial and temporal colocation of LICR and CG flashes. Also a number of CG flash parameters were found to be significantly correlated to rainfall intensity prior to debris flow initiation

Remote extraction and destruction of spread qubit information

Necessary and sufficient conditions for deterministic remote extraction and destruction of qubit information encoded in bipartite states using only local operations and classical communications (LOCC) are presented. The conditions indicate that there is a way to asymmetrically spread qubit information between two parties such that it can be remotely extracted with unit probability at one of the parties but not at the other as long as they are using LOCC. Remote destruction can also be asymmetric between the two parties, but the conditions are incompatible with those for remote extraction.Comment: 14 pages, 2 figure

management of blast and inhalation injury

Key points All patients with facial burns may be suspected of having 'difficult-to-control' airways owing to smoke inhalation injury (SII). Many of them either have an incorrect diagnosis, or mild-to-moderate injury with unrecognised aggravating respiratory failure. For a diagnosis of inhalation injury, it is necessary to follow the patient closely for >48 h. Inhalation injury is a condition with different clinical presentations. Clinical follow-up is necessary to improve patient care, to help guide treatment and to provide clues for therapeutic interventions. Notwithstanding intensive care treatment including airway intubation and mechanical ventilation, many patients with severe inhalation injury remain under-treated. Educational aims To discuss the initial approach and assessment of a patient with SII. To help the reader recognise different clinical pictures of inhalation injury. To outline management and discuss treatment. Summary "Inhalation injury" describes a variety of insults caused by the aspiration of superheated gases, steam or noxious products of incomplete combustion. Inhalation injury involves the entire respiratory system. Early diagnosis based on history and physical examination, in addition to careful monitoring for respiratory complications, is mandatory. As there is no specific treatment for inhalation injury, management involves providing the necessary degree of support required to compensate for upper airway swelling and impairment in gas exchange. Airway intubation and mechanical ventilation may be required while the endobronchial and alveolar mucosa are regenerating. Primary blast injury (BI) is caused by immediate pressure variations, which are the product of rapid sequences of compression and decompression. Secondary and tertiary BI include lesions caused when the subject is thrown against rigid structures or is hit by flying objects. Its diagnosis and therapy follows guidelines for emergency care

Analyzing topographic changes through LiDAR and SfM techniques: assessing the deposition-erosion patterns and estimation of debris-flow volume in the eastern Italian Alps

On 4 August 2015, a very high intensity storm, 31.5 mm in 20 min (94.5 mm/h), hit the massif of Mount Antelao on the Venetian Dolomites (eastern Italian Alps) triggering stony debris flow characterized by high magnitude. It routed along the Ru Secco Creek and progressively reached the resort area and the village of San Vito di Cadore, causing fatalities and damages. The aim of the present research is the study of this debris-flow event by means of pre and post-event topographic data derived by LiDAR (Light Detection and Ranging) and Structure-from-Motion (SfM) photogrammetry technique associated to its occurrence. This study analyzes the Digital Terrain Models (DTMs) derived from LiDAR survey carried out in July 2015 and UAV-SfM data obtained in September 2019. The most important step to compare these multi-temporal surveys was the co-registration process, fundamental to guarantee the coherence among the two different surveys. The post-event SfM-DTM of the area routed by debris flow subtracted to the pre-event LiDAR-DTM, provided a DoD (DTM of Difference) that was useful to assess the deposition-erosion patterns and estimate debris-flow volume. Multi-temporal topographical data are important to analyze the phenomenon and its characteristics. This allowed us to more in depth analyzed the debris-flow effects and provide valuable information for the planning of risk prevention measures

Runoff-generated debris flows: Observation of initiation conditions and erosion–deposition dynamics along the channel at Cancia (eastern Italian Alps)

In the Dolomitic region, abundant coarse hillslope sediment is commonly found at the toe of rocky cliffs. Ephemeral channels originate where lower permeability bedrock surfaces concentrate surface runoff. Debris flows initiate along such channels following intense rainfall and determine the progressive erosion and deepening of the channels. Sediment recharge mechanisms include rock fall, dry ravel processes and channel-bank failures. Here we document debris flow activity that took place in an active debris flow basin during the year 2015. The Cancia basin is located on the southwestern slope of Mount Antelao (3264 m a.s.l.) in the dolomitic region of the eastern Italian Alps. The 2.5 km2 basin is incised in dolomitic limestone rocks. The data consist of repeated topographic surveys, distributed rainfall measurements, time-lapse (2 s) videos of two events and pore pressure measurements in the channel bed. During July and August 2015, two debris flow events occurred, following similarly intense rainstorms. We compared rainfall data to existing rainfall triggering thresholds and simulated the hydrological response of the headwater catchment with a distributed model in order to estimate the total and peak water discharge. Our data clearly illustrate how debris entrainment along the channel is the main contributor to the overall mobilized volume and that erosion is dominant when the channel slope exceeds 16°. Further downstream, sediment accumulation and depletion occurred alternately for the two successive events, indicating that sediment availability along the channel also influences the flow behaviour along the prevailing-transport reach. The comparison between monitoring data, topographical analysis and hydrological simulation allows the estimation of the average solid concentration of the two events and suggests that debris availability has a significant influence on the debris flow volume. © 2020 John Wiley & Sons, Ltd

Survival of patients with spinal muscular atrophy type 1

BACKGROUND: Spinal muscular atrophy type 1 (SMA1) is a progressive disease and is usually fatal in the first year of life. METHODS: A retrospective chart review was performed of SMA1 patients and their outcomes according to the following choices: letting nature take its course (NT); tracheostomy and invasive mechanical ventilation (TV); continuous noninvasive respiratory muscle aid (NRA), including noninvasive ventilation; and mechanically assisted cough. RESULTS: Of 194 consecutively referred patients enrolled in this study (103 males, 91 females), NT, TV, and NRA were chosen for 121 (62.3%), 42 (21.7%), and 31 (16%) patients, respectively. Survival at ages 24 and 48 months was higher in TV than NRA users: 95% (95% confidence interval: 81.8%-98.8%) and 67.7% (95% confidence interval: 46.7%-82%) at age 24 months (P < .001) and 89.43% and 45% at age 48 months in the TV and NRA groups, respectively (P < .001). The choice of TV decreased from 50% (1992-1998) to 12.7% (2005-2010) (P < .005) with a nonstatistically significant increase for NT from 50% to 65%. The choice of NRA increased from 8.1% (1999-2004) to 22.7% (2005-2010) (P < .001). CONCLUSIONS: Long-term survival outcome is determined by the choice of the treatment. NRA and TV can prolong survival, with NRA showing a lower survival probability at ages 24 and 48 months. Copyright © 2013 by the American Academy of Pediatrics

Performance and energy-efficient implementation of a smart city application on FPGAs

The continuous growth of modern cities and the request for better quality of life, coupled with the increased availability of computing resources, lead to an increased attention to smart city services. Smart cities promise to deliver a better life to their inhabitants while simultaneously reducing resource requirements and pollution. They are thus perceived as a key enabler to sustainable growth. Out of many other issues, one of the major concerns for most cities in the world is traffic, which leads to a huge waste of time and energy, and to increased pollution. To optimize traffic in cities, one of the first steps is to get accurate information in real time about the traffic flows in the city. This can be achieved through the application of automated video analytics to the video streams provided by a set of cameras distributed throughout the city. Image sequence processing can be performed both peripherally and centrally. In this paper, we argue that, since centralized processing has several advantages in terms of availability, maintainability and cost, it is a very promising strategy to enable effective traffic management even in large cities. However, the computational costs are enormous, and thus require an energy-efficient High-Performance Computing approach. Field Programmable Gate Arrays (FPGAs) provide comparable computational resources to CPUs and GPUs, yet require much lower amounts of energy per operation (around 6$$\times$$ and 10$$\times$$ for the application considered in this case study). They are thus preferred resources to reduce both energy supply and cooling costs in the huge datacenters that will be needed by Smart Cities. In this paper, we describe efficient implementations of high-performance algorithms that can process traffic camera image sequences to provide traffic flow information in real-time at a low energy and power cost

Mantra 2.0: An online collaborative resource for drug mode of action and repurposing by network analysis

Elucidation of molecular targets of a compound (mode of action, MoA) and of its off-targets is a crucial step in drug development. We developed an online collaborative resource (MANTRA 2.0) that supports this process by exploiting similarities between drug-induced transcriptional profiles. Drugs are organised in a network of nodes (drugs) and edges (similarities) highlighting “communities” of drugs sharing a similar MoA. A user can upload gene expression profiles (GEPs) before and after drug treatment in one or multiple cell types. An automated processing pipeline transforms the GEPs into a unique drug ”node” embedded in the drug-network. Visual inspection of the neighbouring drugs and communities helps in revealing its MoA, and to suggest new applications of known drugs (drug repurposing). MANTRA 2.0 allows storing and sharing user-generated network nodes, thus making MANTRA 2.0 a collaborative ever-growing resource