bluuebunny/crossref_metadata_2025 huggingface dataset:
Research and implementation of steel barrel cover rotation correction
Authors: Zhu Tianming , Tian Ziqi , Chen Daliang
Published: December 2022

Given the problems of low efficiency and poor accuracy of manual adjustment of offset position in screen printing of steel barrel cover, an automatic correction method based on machine vision is studied. The mode of upper-lower computers is adopted. For barrel cover with screw holes, Hough circle detection determines the number and position of screw holes and calculates the rotation direction and angle based on the big screw holes as the orientation datum. For barrel cover without screw holes, which is characterized by a steel seal, a minimum area rectangle is adopted to calculate the rotation direction and angle by collecting the location parameters of the width of the rectangle. The lower computer, PLC, controls the servo motor rotation and exchanges data through the Modbus TCP protocol. The results show that the method can adapt to the characteristics of the screw holes and the steel seal. The rotation angle is within (−180°, 180°). The angular error was ± 0.50°. The method meets the requirements of accuracy and stability.
Dynamic Load Mitigation of 3D-printed Triply Periodic Minimal Surface Structures
Authors: Li Fenglei , Li Bing
Published: December 2022

Three types of triply periodic minimal surface (TPMS) structures are chosen to investigate the quasi-static and dynamic compressive behaviors in this paper. All the TPMS lattices (Primitive, Gyroid, IWP) have the same relative density of 37.5%, and the samples are fabricated by the 3D printing of selective laser melting technique using AlSi10Mg powder. The energy absorption performance and dynamic load mitigation of the 3D printed TPMS structures under three different impact velocities are compared, and the corresponding engineering strain rates are 143 s
−1, 286 s
−1, and 571 s
−1, respectively. The results of numerical simulation indicate that the IWP structure has the highest specific energy absorption (SEA) and plateau stress, followed by the Gyroid structure, and finally the Primitive structure. The SEA of Primitive and Gyroid structures increases with the impact velocity and decreases for IWP structure.
A Single-Channel Speech Enhancement Algorithm Combined with Time-Frequency Mask
Authors: Yu Bowen , Zeng Qingning
Published: December 2022

Aiming at the problem of noise overestimation when the classical single-channel speech enhancement method suppresses noise, single-channel speech enhancement method on the basis of the time-frequency mask is put forward to improve the quality of speech enhancement and separation. First, we estimate the noise and prior signal-to-noise ratio from the noisy speech, calculate the time-frequency mask and finally combine noisy speech synthesis to enhance the speech. Adaptive time-frequency mask combines IBM and IRM to avoid over-suppressing noise. In this paper, noisy speech is processed by an improved time-frequency mask combined with SNR. The algorithm combines the advantages of the single-channel algorithm and time-frequency mask. The experimental results indicate that this method significantly improves the signal-to-noise ratio, is robust, and is easy to use.
Research on Remote Fault Diagnosis System of Harvester
Authors: Zang Chongquan , Wei Xinhua , Li Lin , Hu Cong , Tong Hao
Published: December 2022

The structure of combined harvester is complex, and its operation process includes many processes. There is material transportation between each process, so blocking faults often occur. The blockage fault of combined harvester will seriously affect the efficiency of working and harvest quality, so this paper designs a remote diagnosis system of blockage fault of combined harvester. The system can carry out remote monitoring, fault diagnosis and fault alarm for the operation status of the combine, and also provide information management and other functions, which can effectively carry out remote maintenance services. This paper presents an IPSO-BP fault diagnosis model, which is tested by simulation test. The results show that the accuracy of fault prediction by this method is 97.78%. Compared with BP neural network model and PSO-BP model, the accuracy of fault prediction is improved by 5.28% and 13.45%, meeting the fault diagnosis requirements of combined harvester.
Simulation Research on Interdigitated Electrodes based sensors in water solution monitoring
Authors: Li Manman , Lv Yiwen , Jin Yan , Li Yigui
Published: December 2022

Interdigitated electrodes (IDEs) based sensors have the advantages of being rapid and accurate in the electrochemical detection area. In this paper, simulation research on IDEs-based impedance sensors in water solution is performed, and the electric field distribution under different sizes (pairs, finger width, and finger spacing) is compared, while the corresponding impedance in water solution is calculated. As a result, the optimal size of the IDEs (pairs=10, spacing =0.1 mm, width=0.5 mm) is chosen, and impedance changes in a water solution with different conductivities are investigated. This work provides a good theoretical reference for the actual sensor design.
Design of a Two-phase Brushless DC Motor Control System
Authors: Cao Xiangyang , Liu Jinbo , Wang Dongxue , Wu Changzhong , Tian Jiaxin
Published: December 2022

With the depletion of petrochemical resources in the whole region, reducing the dependence on petrochemical energy, and reducing environmental pollution and carbon emissions have become the common goal of the world. Pure electric vehicles are a kind of new energy vehicle. Compared with fuel vehicles and other types of electric vehicles, they have high energy utilization efficiency, low price, and less pollution emission. Therefore, this paper will discuss the structure, working principle, and control system of the two-phase brushless DC motor and put forward the two-phase four-bridge arm drive scheme to improve the voltage utilization rate and achieve more environmentally friendly and efficient electric energy application.
Research on Hydraulic Servo Valve Control Based on Fuzzy RBF
Authors: Qi Wei , Yang Bo , Chao Yu
Published: December 2022

Aiming at the problems of low control precision and slow response speed of traditional control of actuators in hydraulic systems, the mathematical model of the valve-controlled cylinder is established as the research object, and the control strategy of fuzzy RBF neural network is proposed to control hydraulic servo valves On the basis of traditional fuzzy control, fuzzy control and RBF neural network control are integrated. According to the mathematical model of the system, a tracking controller is designed to realize precise control and real-time feedback of the valve-controlled cylinder system. The simulation results show that compared with traditional PID and fuzzy PID systems, the fuzzy RBF neural network strategy has high control precision, fast response speed, better robustness, and stability.
Analysis of Suspension Control Strategy of Wheel-track Composite Amphibious Vehicle Based on AMESim-Simulink
Authors: Gao Xue , Chang Yukang , Cai Tong , Xu Haijun
Published: December 2022

Amphibious vehicles are an important unit in amphibious transportation. However, the problem of vertical load control of amphibious vehicles on soft roads such as tidal flats and swamps still needs to be solved urgently. Based on a new configuration of wheel-track composite amphibious vehicle (W-TCAV), the coupling relationship between suspension control and vertical load on soft roads is analyzed, and its 1/8 hydraulic system of hydro-pneumatic suspensions is established; Under the condition of known vertical load distribution range, based on the AMESim-Simulink co-simulation platform, the control and tracking effects of two different control strategies are compared and analyzed. The simulation results show that compared with the PID control strategy, the effect of fuzzy PID control on the suspension hydraulic system is more desired, the control response speed to the desired vertical load is faster, and the tracking accuracy is higher. It provides a better control scheme for the suspension system and vertical load control of the W-TCAV.
Research on Electric Control Brake System Based on Railway Vehicle
Authors: Zhang Shixi , Lin Yanfei , Zhao Li , Zhao Guorui , Chen Ruikun , Li Qingxuan
Published: December 2022

The trackless train may be mixed with other vehicles in the city. Therefore, developing a vehicle braking system with high reliability, fast response, and powerful braking force is necessary. In this research, the chip module control is added to each control part to realize rapid electric signal collection and response, and then the pneumatic control of each actuator is used to realize rapid and flexible electric braking control of the vehicle. The braking system has been tested on the test bench in the factory, and its response speed and braking effect have increased by 10% compared with the traditional bus braking system. When the performance test is carried out on the real vehicle, the braking effect is also improved by nearly 10%. Through the design of the braking system, the braking system of domestic trackless trains can be perfectly solved.
Simulation Research on Ship-borne PMSM Speed Regulation Control System Based on Fuzzy PID Control
Authors: Zhu Zhifeng , Chang Liwen , Pan Shuguo
Published: December 2022

As the important actuator of ship-borne electromechanical equipment such as offshore cranes, the control system of Permanent-magnet synchronous motor (PMSM) is a complex system that features nonlinearity, time-varying parameters, and multi-variable coupling. Due to working in a swing environment, the ship-borne PMSM speed regulation control system is confronted with some problems, such as abrupt load change, external interference signals, motor parameters change, and given signals change frequently. To improve the control performance, this study designs the 2-dimensional Fuzzy PID controller and builds the control system simulation model with a double closed-loop structure in the MATLAB/Simulink. By comparing the control system under various simulation situations, the simulation findings demonstrate that the control system using the Fuzzy PID controller far outperforms the PID controller in terms of control indicators such as stability, tracking ability, and anti-disturbance ability, which can better adapt to working in swing environment.
The powering systems of the CMS tracker for HL-LHC
Authors: Paoletti S.
Published: December 2022

The upgraded CMS tracker for HL-LHC is going to require more than 200 kW power. Two different powering strategies are being adopted for the Inner Tracker and the Outer Tracker. The talk describes the two powering schemes and discusses their intrinsic constrains. Specifications for the powering units and for the cables of the two systems are outlined in combination to preliminary results with prototypes.
Edge-TCT evaluation of high voltage-CMOS test structures with unprecedented breakdown voltage for high radiation tolerance
Authors: Wade B. , Franks M. , Hammerich J. , Karim N. , Powell S. , Vilella E. , Zhang C.
Published: December 2022

This paper presents the edge Transient Current Technique (eTCT) measurements of passive test-structures on the UKRI-MPW0 pixel chip, a 280 µm thick proof-of-concept High Voltage-CMOS (HV-CMOS) device designed and fabricated in the LFoundry 150 nm technology node with a nominal substrate resistivity of 1.9 kΩ cm. Samples were irradiated up to 1 × 1016 1 MeV neq cm−2 with neutrons to observe the change in depletion depth and effective doping concentration with irradiation. A depletion depth of the sensor was found to be ≈50 µm at ≈−400 V at 1 × 1016 1 MeV neq cm−2. A stable damage introduction rate (g

c
) was also calculated to be 0.011 ± 0.002 cm−1.
The Role of Food Waste Management in Green City Development
Authors: Sholihah Salma Mar’atus , Rachma Tia Rizka Nuzula , Khasanah Uswatun
Published: December 2022

Food waste generation is a severe problem in Indonesia today. Providing food waste processing facilities that are evenly distributed and reach service areas is essential. This step can lead to developing green cities that harmonize the circular economy and ecological civil aspects. This study aims to identify the location of food waste processing and the range of services to the service area (community settlements). The method used is spatial analysis. The research location is in Ciamis Regency. The results showed that currently, there are 58 locations spread over 24 sub-districts in Ciamis Regency. Food waste processing facilities have not been spread evenly because three districts still do not have waste processing facilities. The number of existing waste processing facilities is not evenly distributed. If viewed from the coverage of the service area (settlement), the existing food waste processing facilities can only meet 23.58% of the existing residential area. Collaboration between the government, the community, and the private sector is needed to build food waste processing facilities that are evenly distributed and reach all service areas. The concept of a circular economy in the food waste management system must be considered to create sustainable food waste management.
Sustainability of Slum Upgraded Area, Case of Mojosongo, Surakarta, Indonesia
Authors: Sunarti S , Yuliastuti Nany , Purwanto Annisa Amellia , Putri Kharunia
Published: December 2022

Sustainable development is a challenge in urban development, especially in a slum area. Management of slum is not optimal, and several slums become slums again after upgrading due to the absence of environmental management, such as Mojosongo Housing, Surakarta City, Indonesia. This article aims to create policy recommendations for environmental quality improvement in slum. The research uses a quantitative method. Secondary data were obtained from related agencies regarding environmental conditions, population data, and policies related to slum management. Primary data was collected via observation and questionnaires to 30 respondents, consisting of natives and immigrants in Mojosongo Housing. The analysis technique uses a comparative analysis of data and literature review. The results show that social and economic aspects have been proven to cause a decrease in environmental quality. The challenge of slum management in strategic areas to be sustainable is via community empowerment of social and economic aspects of livelihoods. In addition, supervision and control of development for the public interest are recommended to be more effective by applying police power (an instrument of zoning regulation) and a taxation mechanism.
Water Quality Status and Water Quality Index of Selulu Reservoir, East Kalimantan, Indonesia
Authors: Pramaningsih Vita , Purwanto Agus Dwi , Yuliawati Ratna , Kurniawan Deny
Published: December 2022

Selulu Reservoir is located in Waru District, North Panajam Paser Regency. It is one of the tourist destinations in supporting the tourism sector. Land use changes and urbanization have potential impacts on the environment. This study aimed to determine Water Quality Status and Water Quality Index (WQI) in Selulu Reservoir. Hopefully, the result will become the basis for future reservoir management to keep the water quality well. The method in this study used the survey method. These research steps include surveys, water samples, laboratory analysis, and data analysis. Parameters analyzed include temperature, pH, BOD, COD, and DO. The results showed that the reservoir’s water quality in all samples still met the standard, except for pH at point 3. The difference fluctuating value found in COD at point 3, although it still meets the standard. This location is close to residential areas that dump their waste into the reservoir. The Water Quality Status of the reservoir still meets the standards, and WQI is in the excellent category. This is due to the dominant land use of forest and plantations with few settlements around the reservoir, domestic waste is small, and the reservoir capacity is still supportive. Management is needed to maintain reservoir water quality in the future.
Velcro Product Design with Biomimicry Approaches
Authors: Hapsari Filia Nauli , Purwaningsih Ratna , Azzahra Faradhina , Sari Diana Puspita
Published: December 2022

Nature has experienced so many adjustments throughout its life cycle, such as evolutions, climate change, and natural selection, and it still manages to exist today. Therefore, it will be an excellent example to be imitated into a product or process since it is most likely sustainable and comply human needs. Imitating nature’s process, design, or system is called Biomimicry Approach. In this research, researchers develop a new design for Velcro. Velcro is a fastener that consists of 2 parts: hook and loop. Both parts are made of nylon thread and will be fastened together. Current Velcro products are not durable because of the design and also materials. It can be easily wrinkled and damage the fabric it is glued. This study aims to develop Velcro design to have a sustainable design using the technical steps in each biomimicry design spiral methodology stage. Researchers used Biomimicry Approach to find the best development for the Velcro product and generate a conceptual design for Velcro. The natural model used in the conceptual design was a Lentinula edodes (shitake mushroom). The design assessment indicator used were von mises stress, safety factory, and displacement. The results showed that the development design of Velcro with the Biomimicry Design Spiral Approach was acceptable and safe.
Potential Distribution of Skipjack Tuna Using MODIS Satellite Imagery in The Southern Waters of West Java - Banten
Authors: Suhermat Mamat , Dimyati Muhammad , Supriatna Supriatna , Martono
Published: December 2022

The West Java southern waters - Banten is among the skipjack tuna Katsiuwonus Pelamis distribution areas. It is well known that the skipjack tuna potential distribution is influenced by the environmental circumstances of the waters. This study was performed to establish the potential distribution of skipjack tuna in the West Java southern waters– Banten to support the potential management program of marine fishery resources. The data used consisted of skipjack tuna catch position, sea surface temperature, and chlorophyll-a concentrations from June 2019 to August 2019. Descriptive analysis and maximum entropy (maxent) model were applied to analyze skipjack tuna’s potential distribution. The results revealed that the potential area of skipjack tuna is scattered in parts of the southern waters of West Java - Banten, with a validation test of the model performance of 0.92 (excellent).
The Performance of Companies in Assisting the Environment By Issuing Green Bond
Authors: Tua Pandior Benget Namora , Rokhim Rofikoh
Published: December 2022

Besides as well as a way for companies to raise money and for investors to differentiate their portfolios, as should be one of the purposes of the issuance of Green Bonds to mitigate a decrease in carbon emissions does not accompany climate change, the expansion in the issuance of Green Bonds. The emergence of green bonds evidences investor interest in financial and environmental instruments. The business must continue to operate well to satisfy investor expectations. Using the Purposive Sampling technique, this study examines 89 companies for the impact of several financial parameters on the success of businesses that issue green bonds using panel data regression and multiple linear regression techniques. The findings demonstrated that the factors Equity Multiplier, Total Asset Turnover, and Profit Margin significantly impacted the company’s performance as measured by the ROE variable. The findings also demonstrate that issuers of Green Bonds frequently use their business activities to boost their performance.
Community Resilient from Anak Krakatau Eruption: Lesson Learn from The Tale of Lampung Submerged to Increase Environmental Awareness
Authors: Firdaus Azhar , Afiff Suraya Abdulwahab , Herdiansyah
Published: December 2022

Natural disasters in Indonesia have a high frequency because a whole land and sea in Indonesia be hemmed in tectonic and volcanic plates. Some natural disasters are not caused by those plates, such as landslides, floods, hurricanes, etcetera. In the research location (beginning of 2018), there was a natural disaster called the silent tsunami caused by landslides at Mount Anak Krakatau in the middle of the ocean. In large quantities, these landslides produced high waves in the coastal area in Lampung and Banten, and there was no early warning system for this silent tsunami. The article aims to study the local knowledge related to the Anak Krakatau Volcano eruption in the coastal around it. Also, the article will present the history of Anak Krakatau volcanoes and the lessons from communities within the local knowledge. For example, it is from the Tale of Lampung Submerged as secondary data for this article. This tale will be analyzed how this tale could understand the local knowledge in terms of the Mount Krakatau eruption. This local knowledge will help the communities’ strategies to face natural disasters and how the recovery process is carried out to increase environmental awareness.
Environmental Self-Identity and Pro-Environmental Behavior in Climate Change Issue: Mediation Effect of Belief in Global Warming and Guilty Feeling
Authors: Shadiqi Muhammad Abdan , Djuwita Ratna , Febriana Silvia Kristanti Tri , Septiannisa Lulu , Wildi Muhammad , Rahmawati Yuli
Published: December 2022

There are several arguments about the role of identity factors behind someone’s pro-environmental behavior (PEB) encountering climate change. The authors assumed other factors might explain the correlation between identity factors and PEB. This study aims to examine the mediating effect of belief in global warming and guilty feeling on the correlation between environmental self-identity and pro-environmental behavior related to climate change issues. We conducted a cross-sectional survey involving 202 university students selected using the purposive sampling method. Using multiple mediators of model 4 from PROCESS Macro Hayes, the result shows that environmental self-identity is the most decisive variable in predicting PEB. Belief in global warming is also a significant PEB predictor, while the guilty feeling is insignificant. The mediation model analysis showed that belief in global warming partly mediated the correlation between environmental self-identity and PEB, and the guilty feeling was not a significant mediator. This finding explains that self-identity as an environmentalist is directly related to PEB, or it could also be mediated through the belief in global warming. This study implies that encouraging students to be pro-environmentalist and developing the belief in current climate change is essential to increase students’ PEB.
The Effectiveness of Community Participation in Urban Water Supply: A Narrative Review
Authors: Purba Debora E. , Wahyu Agung Minto
Published: December 2022

Debates on the effectiveness of top-down versus bottom-up approaches in water management in urban areas are still ongoing. This study examines the effectiveness of community participation as a bottom-up approach. The narrative review is employed to describe 16 cases of community participation. Three themes emerge from the case studies: the success story and failure of community participation from outside of Indonesia, lessons learned and best practices of community participation from Indonesia, and self-supply as an alternative water provision. Then a discussion of the findings based on the themes found in the literature was carried out. The study found that community participation would be successful if the participatory elements were satisfied, including sufficient capacity and knowledge of the community involved to ensure meaningful participation, involving local government in the education of how to manage and conserve water supply, and involving women in project sustainability. Hence, a pure community participation approach, particularly in disadvantaged urban areas, cannot be achieved. Therefore, a holistic approach combining a top-down and a bottom-up approach is recommended. Self-supply water provision emerged as another method that has largely been ignored by the government and academia but serves as a common practice, particularly in developing countries.
New kind of IoT platform for Smart City by innovative procurement procedure
Authors: Vehviläinen M , Vainio T
Published: December 2022

The City of Tampere, like many other cities, has opened databases available to citizens and businesses. The information has been opened using existing information channels. Since the city typically works in silos, there is also open data made available in silos. The process by which information is first collected and then made openly available does not serve the needs of a digitalized society. Since the problem is common, measures to remedy it had been set as an objective under the EU Smart City theme, from which the City of Tampere received funding. The aim was to design and acquire an information system capable of both collecting and distributing information to both internal and external users. The specific objectives were to make information flow between the actions of the city and to facilitate the participation of the residents in the decision, rather than simply being the recipients of the information. Innovative procurement was applied to acquire a completely new type of information system. Hackathons were used to refine the characteristics of the acquisition with the participation of multi-disciplinary consortia. The project resulted in an IoT platform for the City of Tampere, which streamlines information processing and helps cooperation within the city’s departments. The model of public procurement because of the project is generally valid and useful in other cities as well.
Socially and culturally sustainable public participation in urban development: Map questionnaire as a bridge-building tool in Kontula shopping mall
Authors: Nummi P , Harsia E
Published: December 2022

Social sustainability is a prerequisite for legitimate public participation. Currently, multilingualism and multiculturalism place particular demands on participation methods and processes. This article presents a case study where entrepreneurs with an immigrant background were engaged in the development process of Kontula shopping mall in Helsinki, Finland. The results show that an existing digital participation tool, specifically a map questionnaire can be utilized in a novel way in a multicultural context to build a bridge between this marginalized group and urban development. New skills and tailored methods are required to support the participation of immigrant entrepreneurs.
The modern tropical architecture and social-environmental classification - An analysis of the Prefeito Mendes de Moraes Housing Complex
Authors: Calazães M B O , Di Trapano P , Bastos L E G , Pecly M L V
Published: December 2022

Modern architecture took different forms and shapes around the world, trying, even though its well defined concepts and values, to find out ideal measures and answers to a technological contemporary world. In the tropics this architecture is largely related to the construction of strong and modern governmental institutions. In this cenarium, social housing and adaptation to the climate were really popular topics, being carefully cared for by Brazilian modernists. The present study analyzes the residential block A from the social housing complex Conjunto Habitacional Prefeito Mendes de Moraes, based on the requirements of a social-environmental classification instrument created specifically for Brazilians construction sector, called Selo Casa Azul. The building to be analyzed is an icon of modern architecture, and part of a pioneering experience in the construction of a “neighborhood unit”. Designed by Afonso Reidy and Carmen Portinho in 1946 It contains 272 apartments grouped in one single 260 meters long block and a range of design solutions regarding thermal comfort by passive solutions. For the realization of the work iconographic material was collected and a site visit was taken. As a result, it was possible to observe the topicality of the building, despite the many years that separate the project from the creation of the seal, and the consequent changes in the construction technologies and benchmarks.
Combining BIM & GIS Information to Simulate Circularity of Building Stocks in a City—A Case Study of Taipei City
Authors: Chang Y T , Sierra E M , Hsieh S H
Published: December 2022

Building stocks in cities have consumed a large amount of energy and resources globally, resulting in serious greenhouse gas pollution and environmental problems. As a circular economy has become one of the effective solutions to current environmental problems, energy and material circularity indicators of building stocks in cities become important instruments for city planners in creating sustainable and resilient cities. However, such evaluation requires a high level of integration of both spatial and attribute information of both buildings and cities. A highly integrated system is required to produce reliable analysis results. This study aims to create an evaluation tool for city planners through utilizing information contained via Building Information Modeling and Geographic Information System. Through this tool, planners and decision makers can understand current and future circularity and environmental impacts of building stocks in cities and therefore can propose the most suitable planning and governance strategies and policies. Through visualization of simulation results on an information platform, the awareness of a circular city could also be raised. Taipei city and its city master plan are used as a case study for validation of the proposed tool.
Successful social entrepreneurship and its potential contribution to more sustainable cities and built environments
Authors: Antuña-Rozado C , García-Navarro J
Published: December 2022

Globally, social entrepreneurship has caught the attention of academics and researchers, and there is a growing body of knowledge on how it differs from traditional entrepreneurship and where its main challenges lie. In Finland, for example, the number of social enterprises has been growing consistently since 2010. The Finnish case is particularly intriguing because of the country’s wide social coverage, which on a first approach, might lead to the assumption that social enterprises are not “so necessary” in Finland. However, the matter is more complex than it initially appears. Moreover, the European commitment to make the transition to a just and green society, in compliance with the ambitious objectives of the European Green Deal, as well as to materialize the so-called economy of wellbeing, exerts pressure on public administrations that perhaps social enterprises can help alleviate.

Despite many open questions, successful social enterprises-that is, those whose mission, strategy, and impact measurement are strongly aligned-can be critical in addressing social or environmental issues that remain largely unaddressed by other actors, whether public or private, in any field, without compromising their growth potential and their ability to attract interested investors.

Considering, on the one hand, the wide range of opportunities offered by the built environment in terms of open challenges; and on the other hand, the fact that in the future there will be more pressure on companies to be more socially responsible, it may be worth looking at how social enterprises can help close these gaps.

To encourage the contribution of social enterprises to more sustainable cities and built environments, this document will discuss what successful social entrepreneurship looks like and show a couple of examples of social enterprises from the UK and Norway, one operating in the affordable housing sector and the other dedicated to sustainable urban development.
Building data models and data sharing. Purpose, approaches, and a case study on explainable demand response
Authors: Sakkas Nikos , Chaniotaki Christina , Sakkas Nikitas
Published: December 2022

There are several approaches to building data modelling and there is a well-established rationale for the various related standards emerging in the area. In this work we acknowledge the importance of these approaches but also discuss their limitations. To this extent we draw the line between open data and open sharing and discuss its relevance. We also introduce a case study of a demand response application integrated with a XAI (explainable artificial intelligence) demand forecasting and we use it to practically highlight how open data and open sharing features interplay and integrate. We also discuss how open building model design will need to develop, so as to account for vital, in some cases, explainability information.
Maximum spread of graphs and bipartite graphs
Authors: Breen Jane , Riasanovsky Alex W. N. , Tait Michael , Urschel John
Published: December 2022

Given any graph

G
G

, the spread of

G
G

is the maximum difference between any two eigenvalues of the adjacency matrix of

G
G

. In this paper, we resolve a pair of 20-year-old conjectures of Gregory, Hershkowitz, and Kirkland regarding the spread of graphs. The first states that for all positive integers

n
n

, the

n
n

-vertex graph

G
G

that maximizes spread is the join of a clique and an independent set, with

⌊
2
n

/

3
⌋

\lfloor 2n/3 \rfloor

and

⌈
n

/

3
⌉

\lceil n/3 \rceil

vertices, respectively. Using techniques from the theory of graph limits and numerical analysis, we prove this claim for all

n
n

sufficiently large. As an intermediate step, we prove an analogous result for a family of operators in the Hilbert space over

L

2

[
0
,
1
]

\mathscr {L}^2[0,1]

. The second conjecture claims that for any fixed

m
≤

n
2

/

4

m \leq n^2/4

, if

G
G

maximizes spread over all

n
n

-vertex graphs with

m
m

edges, then

G
G

is bipartite. We prove an asymptotic version of this conjecture. Furthermore, we construct an infinite family of counterexamples, which shows that our asymptotic solution is tight up to lower-order error terms.
ISAnalytics enables longitudinal and high-throughput clonal tracking studies in hematopoietic stem cell gene therapy applications
Authors: Pais Giulia , Spinozzi Giulio , Cesana Daniela , Benedicenti Fabrizio , Albertini Alessandra , Bernardo Maria Ester , Gentner Bernhard , Montini Eugenio , Calabria Andrea
Published: December 2022

Longitudinal clonal tracking studies based on high-throughput sequencing technologies supported safety and long-term efficacy and unraveled hematopoietic reconstitution in many gene therapy applications with unprecedented resolution. However, monitoring patients over a decade-long follow-up entails a constant increase of large data volume with the emergence of critical computational challenges, unfortunately not addressed by currently available tools. Here we present ISAnalytics, a new R package for comprehensive and high-throughput clonal tracking studies using vector integration sites as markers of cellular identity. Once identified the clones externally from ISAnalytics and imported in the package, a wide range of implemented functionalities are available to users for assessing the safety and long-term efficacy of the treatment, here described in a clinical trial use case for Hurler disease, and for supporting hematopoietic stem cell biology in vivo with longitudinal analysis of clones over time, proliferation and differentiation. ISAnalytics is conceived to be metadata-driven, enabling users to focus on biological questions and hypotheses rather than on computational aspects. ISAnalytics can be fully integrated within laboratory workflows and standard procedures. Moreover, ISAnalytics is designed with efficient and scalable data structures, benchmarked with previous methods, and grants reproducibility and full analytical control through interactive web-reports and a module with Shiny interface. The implemented functionalities are flexible for all viral vector-based clonal tracking applications as well as genetic barcoding or cancer immunotherapies.
GraphLncLoc: long non-coding RNA subcellular localization prediction using graph convolutional networks based on sequence to graph transformation
Authors: Li Min , Zhao Baoying , Yin Rui , Lu Chengqian , Guo Fei , Zeng Min
Published: December 2022

The subcellular localization of long non-coding RNAs (lncRNAs) is crucial for understanding lncRNA functions. Most of existing lncRNA subcellular localization prediction methods use k-mer frequency features to encode lncRNA sequences. However, k-mer frequency features lose sequence order information and fail to capture sequence patterns and motifs of different lengths. In this paper, we proposed GraphLncLoc, a graph convolutional network-based deep learning model, for predicting lncRNA subcellular localization. Unlike previous studies encoding lncRNA sequences by using k-mer frequency features, GraphLncLoc transforms lncRNA sequences into de Bruijn graphs, which transforms the sequence classification problem into a graph classification problem. To extract the high-level features from the de Bruijn graph, GraphLncLoc employs graph convolutional networks to learn latent representations. Then, the high-level feature vectors derived from de Bruijn graph are fed into a fully connected layer to perform the prediction task. Extensive experiments show that GraphLncLoc achieves better performance than traditional machine learning models and existing predictors. In addition, our analyses show that transforming sequences into graphs has more distinguishable features and is more robust than k-mer frequency features. The case study shows that GraphLncLoc can uncover important motifs for nucleus subcellular localization. GraphLncLoc web server is available at http://csuligroup.com:8000/GraphLncLoc/.
CODA: a combo-Seq data analysis workflow
Authors: Nazzari Marta , Hauser Duncan , van Herwijnen Marcel , Romitti Mírian , Carvalho Daniel J , Kip Anna M , Caiment Florian
Published: December 2022

The analysis of the combined mRNA and miRNA content of a biological sample can be of interest for answering several research questions, like biomarkers discovery, or mRNA–miRNA interactions. However, the process is costly and time-consuming, separate libraries need to be prepared and sequenced on different flowcells. Combo-Seq is a library prep kit that allows us to prepare combined mRNA–miRNA libraries starting from very low total RNA. To date, no dedicated bioinformatics method exists for the processing of Combo-Seq data. In this paper, we describe CODA (Combo-seq Data Analysis), a workflow specifically developed for the processing of Combo-Seq data that employs existing free-to-use tools. We compare CODA with exceRpt, the pipeline suggested by the kit manufacturer for this purpose. We also evaluate how Combo-Seq libraries analysed with CODA perform compared with conventional poly(A) and small RNA libraries prepared from the same samples. We show that using CODA more successfully trimmed reads are recovered compared with exceRpt, and the difference is more dramatic with short sequencing reads. We demonstrate how Combo-Seq identifies as many genes and fewer miRNAs compared to the standard libraries, and how miRNA validation favours conventional small RNA libraries over Combo-Seq. The CODA code is available at https://github.com/marta-nazzari/CODA.
Expert-Level Immunofixation Electrophoresis Image Recognition based on Explainable and Generalizable Deep Learning
Authors: Hu Honghua , Xu Wei , Jiang Ting , Cheng Yuheng , Tao Xiaoyan , Liu Wenna , Jian Meiling , Li Kang , Wang Guotai
Published: December 2022

Background

Immunofixation electrophoresis (IFE) is important for diagnosis of plasma cell disorders (PCDs). Manual analysis of IFE images is time-consuming and potentially subjective. An artificial intelligence (AI) system for automatic and accurate IFE image recognition is desirable.

Methods

In total, 12 703 expert-annotated IFE images (9182 from a new IFE imaging system and 3521 from an old one) were used to develop and test an AI system that was an ensemble of 3 deep neural networks. The model takes an IFE image as input and predicts the presence of 8 basic patterns (IgA-, IgA-, IgG-, IgG-, IgM-, IgM-, light chain and ) and their combinations. Score-based class activation maps (Score-CAMs) were used for visual explanation of the models prediction.

Results

The AI model achieved an average accuracy, sensitivity, and specificity of 99.82, 93.17, and 99.93, respectively, for detection of the 8 basic patterns, which outperformed 4 junior experts with 1 years experience and was comparable to a senior expert with 5 years experience. The Score-CAMs gave a reasonable visual explanation of the prediction by highlighting the target aligned regions in the bands and indicating potentially unreliable predictions. When trained with only the new system images, the models performance was still higher than junior experts on both the new and old IFE systems, with average accuracy of 99.91 and 99.81, respectively.

Conclusions

Our AI system achieved human-level performance in automatic recognition of IFE images, with high explainability and generalizability. It has the potential to improve the efficiency and reliability of diagnosis of PCDs.
Interactive Visualization of Large Point Clouds Using an Autotuning Multiresolution Out-Of-Core Strategy
Authors: Teijeiro Diego , Amor Margarita , Doallo Ramón , Deibe David
Published: December 2022

Due to the increasingly large amount of data acquired into point clouds, from LiDAR (Light Detection and Ranging) sensors and 2D/3D sensors, massive point clouds processing has become a topic with high interest for several fields. Current client-server applications usually use multiresolution out-of-core proposals; nevertheless, the construction of the data structures required is very time-consuming. Furthermore, these multiresolution approaches present problems regarding point density changes between different levels of detail and artifacts due to the rendering of elements entering and leaving the field of view. We present an autotuning multiresolution out-of-core strategy to avoid these problems. Other objectives are reducing loading times while maintaining low memory requirements, high visualization quality and achieving interactive visualization of massive point clouds. This strategy identifies certain parameters, called performance parameters, and defines a set of premises to obtain the goals mentioned above. The optimal parameter values depend on the number of points per cell in the multiresolution structure. We test our proposal in our web-based visualization software designed to work with the structures and storage format used and display massive point clouds achieving interactive visualization of point clouds with more than 27 billion points.
Perceptual Image Hashing Based on Canny Operator and Tensor for Copy-Move Forgery Detection
Authors: Liu Mengqi , Gao Hang , Xia Xiaofan , Gui Suying , Gao Tiegang
Published: December 2022

Copy-move is a common image forgery operation, which copies and moves a block of an image from one position to another place. Image hashing refers to extracting a unique number sequence from the image by using various image features. In practical application, image hashing is used to replace the image itself, which effectively reduces the cost of image storage and computational complexity. In this paper, we propose a novel image hash extraction scheme: constructing image hashing by combining local feature based on Canny operator and global feature based on tensor. In addition, instead of using the traditional correlation coefficient or Hamming distance, a novel method is proposed to calculate the hash distances. A large number of experiments have proved that our image hashing can achieve a better balance between robustness and discrimination with a shorter hash length. What’s more, we can directly locate the forgery areas from the hashing for copy-move forged images.
Neuronal nets and logistic regression analysis provide improved prediction of infective endocarditis compared to the modified Duke Score: a post-hoc analysis of the prospective PRO-ENDOCARDITIS study
Authors: Vogel L , Dykun I , Totzeck M , Rassaf T , Mahabadi A
Published: December 2022

Introduction

The modified Duke score is the currently recommended diagnostic algorithm in suspected infective endocarditis (IE). The categorization in major and minor criteria enables an easy clinical application, but may not optimally utilize individual patient's information. In contrast, detailed statistical evaluation of multiple characteristics using artificial intelligence and logistic regression report improved prediction of various cardiovascular diseases over conventional clinical strategies. We tested the hypothesis that neuronal nets and logistic regression analysis would provide improved prediction of IE as compared to the modified Duke score.

Methods

This post-hoc evaluation of the prospective observational PRO-ENDOCARDITIS study was conducted at the West German Heart and Vascular center between December 2017 and May 2019 and includes 261 patients. Duke criteria and clinical characteristics were prospectively collected. Transesophageal echocardiography (TEE) imaging was evaluated by a blinded cardiologist at a central core-lab. IE as primary endpoint was adjudicated by an independent clinical endpoint committee. The database was divided into a training (70%) and validation cohort (30%). We compared the value of the Duke score, neuronal nets and logistic regression analysis for prediction of the primary endpoint.

Results

The mean age was 60.1±16.1 years, 37.2% were female. In 47 cases, IE was present. The modified Duke score achieved an AUC of 0.863 in the training cohort and 0.913 within the validation cohort. The logistic regression and the neural net exceeded the predictive value in both cohorts (training cohort: 0.992 and 0.986; validation cohort: 0.964, 0.957; for logistic regression and neuronal nets, respectively, Figure 1). Without the use of TEE, the remaining Duke criteria only poorly predicted IE (training cohort: 0.771, 0.951 and 0.938; validation cohort: 0.835, 0.862 and 0.780, for the Duke score, logistic regression and neuronal nets, respectively).

Discussion

Logistic regression analysis and neuronal nets provide improved prediction of IE as compared to the clinically established modified Duke score. Further studies on larger databases are needed to confirm our results and provide algorithms for clinical routine.

Funding Acknowledgement

Type of funding sources: None.