Critical Segments Research Articles

Biking islands in cities: An analysis combining bike trajectory and percolation theory

Bike trajectories generated by the dockless bike-sharing service provides a great opportunity to explore users' travel behavior within the shared mobility transportation ecosystem. This paper proposes a new concept, namely biking islands, defined as geographical areas of interest with a high concentration of bike usage. Leveraging high-resolution trajectory data, biking islands are identified via percolation theory because of its suitability in describing the formation of clusters and critical road segments that have significant influence on biking behavior in an urban context. We showcase our methodology using the bike trajectory dataset provided by a market-leading company and use Shanghai, China as the study area. Results reveal a hierarchical structure of biking islands. With the increase of threshold, the biking islands start to shrink and split into various smaller ones. Larger biking islands are usually located in the central urban area of Shanghai and the Huangpu River acts as a natural barrier that impedes biking continuity across the region. Besides, the formation of biking islands is highly influenced by the surrounding land uses. The proposed concept and methods are not only helpful to understand travel behavior of cyclists and urban structures used for cycling, but also has the potential to support relevant urban and transportation planning, such as identifying designated non-motorized areas for cycling and biking facilities and pinpointing critical road segments that can improve the cycling efficiency of the entire network. Biking islands could be designed as designated areas for cycling where sufficient bike facilities are provided, and/or motorized transport modes are restricted or even prohibited, so as to ensure the convenience and safety of cyclists and support the development of bike-friendly cities.

Flood evacuation and rescue: The identification of critical road segments using whole-landscape features

When studying real-world infrastructure systems as networks, one common avenue of analysis is the identification of critical network elements. These features are often defined as the nodes or edges in a given network that play an outsized role in the structure and functionality of the system. When network systems are under duress, particularly during (or just after) large-scale natural disasters, the continuity of networks is heavily dependent on these critical elements. If the critical features are vulnerable to disruption, the robustness of the network is compromised. The purpose of this paper is to introduce a novel geocomputational method for detecting critical road segments in a post-disaster landscape, with an eye toward human mobility and emergency response. This method accounts for the impacts of non-road landscape features on the overall traversability of an area and is contrasted with traditional critical feature analysis. The developed method provides several advantages, including the ability to produce higher-resolution, higher-fidelity criticality metrics for individual road segments. The paper concludes with a discussion on potential benefits to strategic urban planning, evacuation, and rescue planning during extreme events.

Weighted Multi-attribute Framework to Identify Freeway Incident Hot Spots in a Spatiotemporal Context

The present work used the analytical hierarchy process supported by a machine learning technique (namely random forest variable importance) in a geospatial environment to identify traffic-incident hot spots where seven incident attributes (incident severity level, vehicle type, number of vehicles involved, number of weather condition factors, number of lanes blocked, time period, and incident duration) and incident frequency were considered. Using a frame of raster representation, each factor was ranked and weighted based on the literature, expert surveys, and random forest technique to perform hot spot analysis and generate a critical road index map. Statistical analysis of spatial clustering and hot spot spatial densities was carried out based on Moran’s I method of spatial autocorrelation, Getis–Ord Gi* statistics, and point kernel density. Based on weighted attributes of more than 130,000 incidents from Harris County, Texas, for the period between 2004 and 2013, the method successfully identified critical road segments and highlighted factors that contribute to criticality. The results show that high-severity segments are located in the downtown area during the period of 2004 to 2010, and shifted northwest of the downtown area during the period of 2010 to 2013. The random forest variable importance revealed that the number of lanes blocked along with time periods was the most critical factor affecting the severity of traffic incidents. Though the application of the method was demonstrated using incident database from Harris County, it can be generalized to other cities. Traffic agencies can use the suggested approach to garner and visualize reliable information that ensures better traffic management schemes.

Fatehgarh lacustrine turbidite potential, Barmer Basin, India

Global discovered resources of oil and gas in giant stratigraphic and structural-stratigraphic combination traps have increased by nearly 50% in the last 17 years. Among the biggest contributors are the large discoveries in deepwater turbidite systems in passive margins and rift basins. The current study area is located in the Barmer Basin in northwestern India. Barmer Basin is a prolific petroliferous basin with major oil discoveries in structural plays including Mangala, Bhagyam, and Aishwariya fields. The principal reservoirs in the structural highs are high-quality fluvial sandstones of the Paleocene Fatehgarh Formation. Lacustrine turbidite plays have been discovered in the overlying Paleocene Barmer Hill Formation, albeit with moderate to poor reservoir quality. The potential exists, however, for finding off-structure lacustrine deepwater turbidite plays in the Paleocene Fatehgarh with reservoir quality comparable to the high-quality fluvial facies encountered updip in the structural plays. An integrated approach was adopted to identify stratigraphic entrapments across the basin to chase high-quality Fatehgarh reservoirs. Gross depositional environment maps integrating new geoscientific data were created, followed by well-calibrated seismic geomorphology and seismic facies interpretations to identify the distal lacustrine deepwater turbidite system fed by the updip fluvial Fatehgarh systems. Worldwide, the critical risk elements associated with such plays are reservoir presence, quality, and lateral seal. Geophysical tools like unsupervised seismic waveform classification, spectral decomposition, and seismic inversion were applied to the available seismic data, and the results were integrated with the regional geology and well facies information to derisk the critical risk segments.

Transition Towards Energy Efficient Housing: Detection of The “Weakest Links” In Energy Performance of the Residential Building Stock of Bosnia and Herzegovina

The objective of this paper is to evaluate and distinguish the most critical segments of the residential building stock in Bosnia and Herzegovina in terms of its energy performance, in order to define the guidelines and priorities in the development of the energy efficiency strategies and building refurbishment plans. The research methodology will be explained systematic in the case of the most dominant typology in Bosnia and Herzegovina: the single-family houses built from 1981 to 1991. The analysis will include an overview of the average features for the selected category, which were obtained from the statistical survey and embraces several aspects: urbanism, architecture building physics and heating system. Subsequent methodological steps included the selection of the “representative” or the “typical” buildings, which are characterized by average or the most typical properties of each category within the entire database. This paper will present the analysis, which intend to demonstrate that, according to their potential in terms of possible energy savings, based on the presented improvement measures, the highlighted building typology – the single-family houses of 27 to 37 years of age – can be considered as the most relevant building typology in developing the strategies and plans of the residential building stock refurbishment. This paper is a part of the research on the typology of existing residential buildings in Bosnia and Herzegovina, which was initiated in 2014. Being the first-of-a-kind systematic approach on the subject matter, this research intends to catalyse the shift to the energy efficient housing models in a post-transition and post-conflict country such as Bosnia and Herzegovina.

Strain by the train: Patterns of toad fatalities on a Brazilian Amazonian railroad

Transportation infrastructures are directly responsible for killing billions of animals worldwide. Although the understanding about road impacts have recently increased, the impact of railroads on wildlife has received less attention. The current knowledge concerning the impacts of railroads focuses mainly on large mammals although amphibians might be affected. Our study aims to unravel temporal and spatial patterns of Rhinella toad fatalities on a Brazilian Amazonian railroad, to comprehend how toads are killed and to estimate the magnitude of toad fatalities. Data collection was carried out on foot on an 871-km stretch of the Estrada de Ferro Carajás from 2013 to 2017. We identified different potential causes for fatalities: being run over, desiccated or with barotrauma signs. We estimated a surprisingly high carcass persistence probability of about 38 days. After correcting for the bias from carcass detection and removal, we estimated that approximately 10,000 toads are killed per year (≈ 11 fatalities/km/year). A GLM model showed that toads were more likely to be killed in the dry to wet transition. We identified critical zones of fatalities and prioritized them according to their intensity. The highly critical segments encompass >10% of all fatalities although they cover only 1.5% of the railroad. Our study is the first one to address carcass detection and persistence on railroads and to unravel patterns of fatalities of an amphibian species in a tropical climate. A better understanding of the patterns of animal fatality on railroads is of fundamental importance to manage and mitigate this impact.

Design, Implementation and Testing of a New Mobile Multi-Function Sensing Device for Identifying High-Risk Areas for Bicyclists in Highly Congested Urban Streets

The number of bicycle riders in New York City has been increasing steadily in the past few years. These numbers include private and shared bicycles. NYC bicycle network has been expanded to accommodate this new volume. Although this new infrastructure has reduced the number of cyclists killed or seriously injured (KSI) in some areas, in other areas similar improvements were not observed. This inconsistency of how the number of bicycle crashes varies from one region to another in the city is the primary motivation of this paper. A highly portable and inexpensive sensing device for measuring the distance between a bicycle and lateral objects is designed from scratch and developed. The developed mobile sensing device can also map bicycle trajectories to highlight critical segments where the safe distance from passing vehicles is not respected. This device which is powered by a portable power source is comprised of two ultrasonic sensors namely, a Global Positioning System (GPS) receiver, and a real-time clock (RTC). The sensor is secured inside a custom design 3D printed case. The case can be easily attached to any bicycle including shared Citi Bike bicycles for testing. The final prototype is entirely functional and used to collect sample data to demonstrate its effectiveness to address safety-related problems mentioned above. Finally, a dashboard is created to display collected key information. This key information can be used by researches and agencies for a better understanding of the factors contributing to the safety of bicycle routes.

MACEDONIAN AGRICULTURAL CAPITAL MARKET AND SUPPORTING MECHANISMS: AN OVERVIEW

The Macedonian agricultural capital market is not efficient enough, although there have been some improvements due to the established supporting mechanisms. This paper aims to identify current gaps between agricultural financial services’ and mechanisms’ supply and demand on the agricultural capital market. In this regard, literature and other available secondary sources have been reviewed. Additionally, focused discussions with different stakeholders in the agricultural capital market were conducted, including representatives from the capital demand side (farmers and their associations), and supply side (banks, saving houses, and their associations), as well as supporting institutions and intermediaries (government institutions and donor projects that work towards improvement of farmers’ access to finance in the country). Crediting is one of the key drivers of agricultural and rural development. There are other external financial sources that should be considered, which could contribute in improved capital flow to the agricultural sector. The results revealed critical segments in the agricultural capital market based on the mismatches between the supply and demand for capital and supporting mechanisms, and suggest directions for further improvements of this market. The findings may serve as a baseline for future policy settings and enhancement of a more efficient development of the agricultural capital market in the country.

Crowdsourced Assessment of Inanimate Biotissue Drills: A Valid and Cost-Effective Way to Evaluate Surgical Trainees

Providing feedback to surgical trainees is a critical component for assessment of technical skills, yet remains costly and time consuming. We hypothesize that statistical selection can identify a homogenous group of nonexpert crowdworkers capable of accurately grading inanimate surgical video. Applicants auditioned by grading 9 training videos using the Objective Structured Assessment of Technical Skills (OSATS) tool and an error-based checklist. The summed OSATS, summed errors, and OSATS summary score were tested for outliers using Cronbach's Alpha and single measure intraclass correlation. Accepted crowdworkers then submitted grades for videos in 3 different compositions: full video 1× speed, full video 2× speed, and critical section segmented video. Graders were blinded to this study and a similar statistical analysis was performed. The study was conducted at the University of Pittsburgh Medical Center (Pittsburgh, PA), a tertiary care academic teaching hospital. Thirty-six premedical students participated as crowdworker applicants and 2 surgery experts were compared as the gold-standard. The selected hire intraclass correlation was 0.717 for Total Errors and 0.794 for Total OSATS for the first hire group and 0.800 for Total OSATS and 0.654 for Total Errors for the second hire group. There was very good correlation between full videos at 1× and 2× speed with an interitem statistic of 0.817 for errors and 0.86 for OSATS. Only moderate correlation was found with critical section segments. In 1 year 275hours of inanimate video was graded costing $22.27/video or $1.03/minute. Statistical selection can be used to identify a homogenous cohort of crowdworkers used for grading trainees' inanimate drills. Crowdworkers can distinguish OSATS metrics and errors in full videos at 2× speed but were less consistent with segmented videos. The program is a comparatively cost-effective way to provide feedback to surgical trainees.

Writing out of Ruins

Abstract This hybrid autobiographical/critical paper takes its cue from Yvonne Owuor’s paper in this volume, “Reading our Ruins: A Rough Sketch.” In her piece, Owuor combines a meditation on ruins—as physical, human, social and political—with the perspective of an autopsy, or “seeing for oneself”. In my paper I try to “see for myself” and in myself what it means to consider the ruins of District Six and the responses, individual and institutional, to its violent destruction. More specifically, I try to account for a recent oral history project completed by the District Six Museum which resulted in the writing of a food story and cookbook, District Six Huis Kombuis Tafel: Food and Memory Stories Cookbook (2016). My paper intersperses this critical account with italicised fragments of my own memoir (a work in progress) on District Six, apartheid’s psychic violence, home and food, that relate directly or tangentially to the critical segments. The memoir fragments provide a parallel tale of inner life that at times relates to and supplements the critical discourse, but also at times casts it into doubt.

Event-duration semantics in online sentence processing

Several experiments in Psycholinguistics found evidences of Iterative Coercion, an effect related to the reanalysis of punctual events used in durative contexts triggering an iterative meaning. We argue that this effect is not related to aspectual features, and that event-duration semantics is accessed during Sentence Processing. We ran a self-paced reading experiment in Brazilian Portuguese whose sentences contain events with an average duration of a few minutes. These sentences were inserted in durative contexts that became the experiment’s conditions following a Latin Square design: control condition (minutes), subtractive (seconds), iterative (hours) and habitual (days). Higher RTs were measured at the critical segments of all experimental conditions, except for the habitual context. The results corroborated our hypothesis while defying the psychological reality of habitual coercion. To better observe the habitual coercion condition, we now present a reanalysis of Sampaio et al. (2014) data. The present analysis confirms the results of our tests.***Semântica da duração de eventos no processamento online de sentenças***Diversos experimentos psicolinguísticos encontraram evidências da CoerçãoIterativa, um efeito relacionado à reanálise de eventos pontuais usados emcontextos durativos, que resultam numa leitura iterativa. Nesse trabalho argumentamos que esse efeito não é relacionado a propriedades aspectuais e que a semântica da duração dos eventos é acessada online. Aplicamos um experimento de leitura auto-monitorada em Português Brasileiro, cujas sentenças contém eventos com duração média de alguns minutos. Estas sentenças foram inseridas em quatro condições durativas, seguindo uma distribuição fatorial (quadrado latino):condição controle (minutos), subtrativa (segundos), iterativa (horas) e habitual (dias). Nossos resultados indicam maiores RTs nos segmentos críticos das condições experimentais, exceto em relação a condição habitual. Esses resultados confirmam nossa hipótese, porém, põem em cheque a realidade psicológica da coerção habitual. Assim, para melhor observar os efeitos dessa condição, procedemos uma reanálise dos dados de Sampaio et al. (2014), que finalmente veio confirmar o resultado de nosso teste.

Understanding amyloid fibril formation using protein fragments: structural investigations via vibrational spectroscopy and solid-state NMR.

It is well established that amyloid proteins play a primary role in neurodegenerative diseases. Alzheimer's, Parkinson's, type II diabetes, and Creutzfeldt-Jakob's diseases are part of a wider family encompassing more than 50 human pathologies related to aggregation of proteins. Although this field of research is thoroughly investigated, several aspects of fibrillization remain misunderstood, which in turn slows down, or even impedes, advances in treating and curing amyloidoses. To solve this problem, several research groups have chosen to focus on short fragments of amyloid proteins, sequences that have been found to be of great importance for the amyloid formation process. Studying short peptides allows bypassing the complexity of working with full-length proteins and may provide important information relative to critical segments of amyloid proteins. To this end, efficient biophysical tools are required. In this review, we focus on two essential types of spectroscopic techniques, i.e., vibrational spectroscopy and its derivatives (conventional Raman scattering, deep-UV resonance Raman (DUVRR), Raman optical activity (ROA), surface-enhanced Raman spectroscopy (SERS),tip-enhanced Raman spectroscopy (TERS), infrared (IR) absorption spectroscopy, vibrational circular dichroism (VCD)) and solid-state nuclear magnetic resonance (ssNMR). These techniques revealed powerful to provide a better atomic and molecular comprehension of the amyloidogenic process and fibril structure. This review aims at underlining the information that these techniques can provide and at highlighting their strengths and weaknesses when studying amyloid fragments. Meaningful examples from the literature are provided for each technique, and their complementarity is stressed for the kinetic and structural characterization of amyloid fibril formation.

VMGuards: A Novel Virtual Machine Based Code Protection System with VM Security as the First Class Design Concern

Process-level virtual machine (PVM) based code obfuscation is a viable means for protecting software against runtime code tampering and unauthorized code reverse engineering. PVM-based approaches rely on a VM to determine how instructions of the protected code region are scheduled and executed. Therefore, it is crucial to protect the VM against runtime code tampering that alters the instructions and behavior of the VM. This paper presents VMGuards, a novel PVM-based code protection system that puts the security of VM as the first class design concern. Our approach advances prior work by promoting security of the VM as the first class design constraint. We achieve this by introducing two new instruction sets to protect the internal implementations of critical code segments and the host runtime environment where the VM runs in. Our new instruction sets not only have an identical code structure as standard virtual instructions, but also provide additional information to allow the VM to check whether the critical internal implementation or the runtime environment is affected. We evaluate our approach by using a set of real-life applications. Experimental results show that our approach provides stronger and more fine-grained protection when compared to the state-of-the-art with little extra overhead.

Systems mapping for technology development in CBRN response

PurposeThe purpose of this paper is to develop an EU sociotechnical systems (STSs) map to represent a harmonised concept of operations (CONOPS) as a future development platform for technologies used in multi-services emergency responses to chemical, biological, radiological and nuclear (CBRN) incidents.Design/methodology/approachAcciMaps were developed to locate where technologies are currently used, and opportunities for new technologies. The AcciMaps were iteratively co-designed with end users (fire, ambulance, police and military) across three EU countries (the UK, Finland and Greece). Data were collected using document analysis and interviews with senior ranking (Gold or Silver Command level) representatives of the participating end users.FindingsDespite differences in terminology and between service sectors, consensus was achieved for the command structures (Gold, Silver and Bronze), and Hot Zone responders (specialist blue light responders and blue light responders (BLR)). A control room was included as the communication spine. BLR activities were limited by their scope of practice and available equipment, for example, breathing apparatus. The harmonised EU AcciMap offers a high-level STSs map of CBRN response. Critical segments have been identified which offer opportunities for technology developments that can add value in terms of response capabilities (e.g. tag and trace).Originality/valueA large scale major CBRN incident may need cross-border and cross-professional engagement where efficient interoperability is vital. This research is the first EU consensus of a STS map for CONOPS. It supports future research for technology development, e.g., detection and decontamination equipment design and use, communication, diagnosis and response technologies.

Smart phone applications: Role in agri- information dissemination

Agriculture is a standout amongst the most critical imperative segments of our country. Farming contributes almost around 17.01% of India’s GDP. There are different elements that affected the agriculture development; however the most essential bottlenecks are lack of instant information and drudgery involved in farming practices. To conquer these issues, agriculture should be made more alluring and done smartly. Already there are limited talks on climate smart agriculture, which aims for sustainable increase in agricultural productivity and incomes to meet out the current and future demands. Here, we are examining about how the mobile application can help agriculture development faster and hustle free. There are varieties of mobile applications, utilized over the globe for different segments, including farming, but here the usage is still is limited. We have elaborated various agricultural mobile applications which potentially can be used in farming and allied activities as indicated by their source and usage. In India, there are enormous opportunities for utilizing the smart phones as a part of agribusiness improvement. Its utilization is vital for quick growth and easy access to information to Indian agriculturists, farmers and growers.

Guide them through: An automatic crowd control framework using multi-objective genetic programming

We propose an automatic crowd control framework based on multi-objective optimisation of strategy space using genetic programming. In particular, based on the sensed local crowd densities at different segments, our framework is capable of generating control strategies that guide the individuals on when and where to slow down for optimal overall crowd flow in realtime, quantitatively measured by multiple objectives such as shorter travel time and less congestion along the path. The resulting Pareto-front allows selection of resilient and efficient crowd control strategies in different situations. We first chose a benchmark scenario as used in [1] to test the proposed method. Results show that our method is capable of finding control strategies that are not only quantitatively measured better, but also well aligned with domain experts’ recommendations on effective crowd control such as “slower is faster” and “asymmetric control”. We further applied the proposed framework in actual event planning with approximately 400 participants navigating through a multi-story building. In comparison with the baseline crowd models that do no employ control strategies or just use some hard-coded rules, the proposed framework achieves a shorter travel time and a significantly lower (20%) congestion along critical segments of the path.

Mass balance of arsenic fluxes in rivers impacted by gold mining activities in Paracatu (Minas Gerais State, Brazil).

Arsenic (As) is a dangerous and carcinogenic element and drinking water is its main pathway of human exposure. Gold mines are widely recognized as important sources of As pollution. This work proposes the assessment of As distribution along watersheds surrounding "Morro do Ouro" gold mine (Paracatu, southeastern Brazil). A balance approach between filtered As fluxes (As < 0.45μm) and suspended particulate material (AsSPM) in different river segments was applied. Ultrafiltration procedure was used to categorize As into the following classes: particulate > 0.1μm, colloidal < 0.1μm to > 10kDa, dissolved < 10kDa to > 1kDa, and truly dissolved < 1kDa. By applying this approach, arsenic contributions from mining facilities were quantified in order to identify critical fluvial segments and support decision makers in actions of remediation. The mass balance indicated the occurrence of a decreasing gradient from upstream to downstream: (i) of the As concentrations higher than the limit established by Brazilian law (10μgL-1); (ii) of the ratio between specific fluxes (g Askm-2day-1) and those determined using an uncontaminated watershed (a proxy for estimating the anthropic contribution), from 103 to 101; (iii) of the specific fluxes As < 0.45μm and AsSPM from 102 to 100; and (iv) of the negative balance output minus input for each river segment that suggests As accumulation in sediments along the rivers in both urban and rural areas, mainly due to SPM sedimentation and sorption by Fe oxyhydroxides. Ultrafiltration shattering showed concentrations of decreasing As with particle size; the SPM load (> 0.1μm) was almost one order higher to dissolved load (< 1kDa).

Leakage Detection and Estimation Algorithm for Loss Reduction in Water Piping Networks

Water loss through leaking pipes constitutes a major challenge to the operational service of water utilities. In recent years, increasing concern about the financial loss and environmental pollution caused by leaking pipes has been driving the development of efficient algorithms for detecting leakage in water piping networks. Water distribution networks (WDNs) are disperse in nature with numerous number of nodes and branches. Consequently, identifying the segment(s) of the network and the exact leaking pipelines connected to this segment(s) where higher background leakage outflow occurs is a challenging task. Background leakage concerns the outflow from small cracks or deteriorated joints. In addition, because they are diffuse flow, they are not characterised by quick pressure drop and are not detectable by measuring instruments. Consequently, they go unreported for a long period of time posing a threat to water loss volume. Most of the existing research focuses on the detection and localisation of burst type leakages which are characterised by a sudden pressure drop. In this work, an algorithm for detecting and estimating background leakage in water distribution networks is presented. The algorithm integrates a leakage model into a classical WDN hydraulic model for solving the network leakage flows. The applicability of the developed algorithm is demonstrated on two different water networks. The results of the tested networks are discussed and the solutions obtained show the benefits of the proposed algorithm. A noteworthy evidence is that the algorithm permits the detection of critical segments or pipes of the network experiencing higher leakage outflow and indicates the probable pipes of the network where pressure control can be performed. However, the possible position of pressure control elements along such critical pipes will be addressed in future work.

Multiplex Reverse Transcription-PCR for Simultaneous Surveillance of Influenza A and B Viruses.

Influenza A and B viruses are the causative agents of annual influenza epidemics that can be severe, and influenza A viruses intermittently cause pandemics. Sequence information from influenza virus genomes is instrumental in determining mechanisms underpinning antigenic evolution and antiviral resistance. However, due to sequence diversity and the dynamics of influenza virus evolution, rapid and high-throughput sequencing of influenza viruses remains a challenge. We developed a single-reaction influenza A/B virus (FluA/B) multiplex reverse transcription-PCR (RT-PCR) method that amplifies the most critical genomic segments (hemagglutinin [HA], neuraminidase [NA], and matrix [M]) of seasonal influenza A and B viruses for next-generation sequencing, regardless of viral type, subtype, or lineage. Herein, we demonstrate that the strategy is highly sensitive and robust. The strategy was validated on thousands of seasonal influenza A and B virus-positive specimens using multiple next-generation sequencing platforms.

Gene Therapy with CRISPR/Cas9 Coming to Age for HIV Cure

Gene Therapy with CRISPR/Cas9 Coming to Age for HIV Cure