bluuebunny/crossref_metadata_2025 huggingface dataset:
Phytochemical, Cytotoxicity, and Antimycobacterial Activity Evaluation of Extracts and Compounds from the Stem Bark of Albizia coriaria Welw ex. Oliver
Authors: Obakiro Samuel Baker , Kiprop Ambrose , K’owino Isaac , Andima Moses , Owor Richard Oriko , Chacha Robi , Kigondu Elizabeth
Published: January 2022

Background. Albizia coriaria Welw ex. Oliver (Fabaceae) is one of the plants used by herbalists in the East Africa community to prepare herbal remedies for the management of symptoms of TB. Despite its widespread use, the antimycobacterial activity of this plant was uninvestigated and there was contradicting information regarding its cytotoxicity. Methods. Cytotoxicity (MTT), antimycobacterial activity (MABA), and phytochemical screening were conducted on crude extracts (hexane, chloroform, acetone, and methanol) of the stem bark of A. coriaria. Gas chromatography-mass spectrometry (GC-MS) followed by Fourier transform infrared (FTIR) spectroscopy was carried out on the acetone and methanol extracts. The binding affinities and descriptors of pharmacokinetics and toxicity of the identified compounds were predicted using computational modelling software. Results. The cytotoxic concentrations of all extracts were greater than 1000 μg/mL. The minimum inhibitory concentration of both the acetone and methanol extracts was 1250.0 ± 0.0 μg/mL against M. smegmatis, whereas that against M. tuberculosis was 937.0 ± 442.0 μg/mL and 2500.0 ± 0.0 μg/mL, respectively. Hexane and chloroform extracts were not active against both strains. Alkaloids, triterpenes, flavonoids, tannins, and saponins were the predominant phytochemicals present. GC-MS analysis revealed twenty-eight and nineteen compounds in acetone and methanol extracts, respectively. Among these was hydroquinone, which was previously reported to possess antimycobacterial activity. Seven compounds identified through GC-MS analysis had better binding affinities for the mycobacterial ATPase and polyketide synthase-13 than isoniazid and rifampicin. These compounds also showed variable but promising pharmacokinetic properties with minimum toxicity. Conclusion. There are phytochemicals in A. coriaria stem bark with potential antimycobacterial activity and acceptable cytotoxicity, which can be further explored and optimized for the development of novel antitubercular drugs.
Predicting Coupled Herbs for the Treatment of Hypertension Complicated with Coronary Heart Disease in Real-World Data Based on a Complex Network and Machine Learning
Authors: Huan Jia-Ming , Li Yun-Lun , Zhang Xin , Wei Jian-Liang , Peng Wei , Wang Yi-Min , Su Xiao-Yi , Wang Yi-Fei , Su Wen-Ge
Published: January 2022

Hypertension and coronary heart disease are the most common cardiovascular diseases, and traditional Chinese medicine is applied as an auxiliary treatment for common cardiovascular diseases. This study is based on 3 years of electronic medical record data from the Affiliated Hospital of Shandong University of Traditional Chinese Medicine. A complex network and machine learning algorithm were used to establish a screening model of coupled herbs for the treatment of hypertension complicated with coronary heart disease. A total of 5688 electronic medical records were collected to establish the prescription network and symptom database. The hierarchical network extraction algorithm was used to obtain core herbs. Biological features of herbs were collected from public databases. At the same time, five supervised machine learning models were established based on the biological features of the coupled herbs. Finally, the K-nearest neighbor model was established as a screening model with an AUROC of 91.0%. Seventy coupled herbs for adjuvant treatment of hypertension complicated with coronary heart disease were obtained. It was found that the coupled herbs achieved the purpose of adjuvant therapy mainly by interfering with cytokines and regulating inflammatory and metabolic pathways. These results show that this model can integrate the molecular biological characteristics of herbs, preliminarily screen combinations of herbs, and provide ideas for explaining the value in clinical applications.
Finite Element Prediction on Fracture Load of Femur with Osteogenesis Imperfecta under Various Loading Conditions
Authors: Wanna Soh Bua Chai , Basaruddin Khairul Salleh , Mat Fauziah , Mat Som Mohd Hanafi , Sulaiman Abdul Razak
Published: January 2022

Osteogenesis Imperfecta (OI) is an inherited disorder characterized by extreme bone fragility due to collagen defects. It is an incurable disease. Bone fractures can occur frequently without prior notice, especially among children. Early quantitative prediction of fracture loads due to OI tends to alert patients to avoid unnecessary situations or dangerous conditions. This study is aimed at investigating the fracture loads of femur with OI under various types of loading. Ten finite element models of an OI-affected bone were reconstructed from the normal femur with different bowing angles ranging from 7.5 to 30.0°. The boundary conditions were assigned on an OI-affected femoral head under three types of load: medial-lateral impacts, compression-tension, and internal-external torsions, and various loading direction cases that reflect the stance condition. The fracture load was examined based on the load that can cause bone fracture for each case. The results show that the loads bearable by the femur before fracture were decreased with respect to the increase of OI bowing angles in most of the loading cases. The risk of fracture for the femur with OI was directly proportional to the increase of bowing angles in the frontal plane. This study provides new insights on fracture load prediction in OI-affected bone with respect to various loading types, which could help medical personnel for surgical intervention judgement.
Enhanced constrained local models for gender prediction
Authors: Alsarayreh Ayah , Mohamad Fatma Susilawati
Published: January 2022

Face land-marking, defined as the detection and positioning of distinctive characteristics, is a crucial goal shared by various organizations, ranging from biometric recognition to mental state comprehension. Despite its apparent simplicity, this problem has been extensively investigated because of inherent face variability and a variety of confusing variables such as posture, voice, illumination, and occlusions. In this paper, an integrated mount model is created to increase the power of constrained local models, and a ground-breaking result for feature detection is obtained using this model. Furthermore, four classifiers have been used in the level of gender prediction. The results of the experiment showed that the proposed model performs admirably.
Outage probability computation in multi-backscatter systems with multi-modes of operation
Authors: Do Dinh-Thuan , Le Anh-Tu
Published: January 2022

In this article, we study the outage performance of an ambient multi-backscatter system supported by non-orthogonal multiple access (NOMA) downlink transmission, where legacy users receive information either directly from the base station (BS) or from multiple backscatter devices (BDs) as well. Specifically, we characterize the network connections between the BS and network users into three modes of operation. In the first mode, the BS communicates with the users via the BDs by exploiting NOMA. In the second mode, the BS communicates directly with the users by employing selection combining (SC) beamforming. In the third mode, the users receive signals from both the BS and BDs simultaneously, by using maximal ratio combining (MRC) to combine the BS and BDs links at the users. Consequently, we derive the exact outage expressions of each mode and utilize Monte Carlo simulations to validate the individual exact expressions.
Web and IoT-based hospital location determination with criteria weight analysis
Authors: Hadi Abeer , Abdullah Mahmood Zaki
Published: January 2022

The hospital location selection for COVID-19-infected patients is out to be one of the most critical decisions for healthcare sectors in high-case countries. In this study, optimal urban hospital location selection for COVID-19-infected patients has been done out of multiple alternative locations in city of Baghdad Iraq by introducing a web application system that can find the best site from alternatives by using MEREC and modified technique for order of preference by similarity to ideal solution (TOPSIS) algorithms. MEREC algorithm is utilized to obtain criteria weights and modified TOPSIS for ranking the alternatives. Four criteria are considered with eight alternatives sites. The proposed system has two-part, hardware part (embedded systems) designed by utilizing NEO-6M GPS receiver with ESP8266NodeMCU to obtain coordinate of regions and then, using the HTTP protocol to communicate to submit these data to database server. The second part is the web application developed by PHP, JavaScript, CSS, HTML, and MySQL used to allow the system admin to enter the locations of the alternatives with their criteria into the system to get the best urban hospital location for COVID-19-patients. The results showed effectiveness of overall suggested system and appropriateness of the modified TOPSIS method over the traditional TOPSIS method in ranking the alternative.
Efficient topology discovery protocol using IT-SDN for software-defined wireless sensor network
Authors: Kipongo Joseph , Esenegho Ebenezer , Swart Theo G.
Published: January 2022

The internet of things (IoT) and wireless sensor networks (WSNs) are two promising technologies for supporting new services and applications. However, because IoT and WSN entail interaction and transaction of device topology discovery protocols, WSN facing some challenges. Topology discovery (TD) is important for WSN in IoT since sensor nodes (SNs) are the main points of this network. Networking these SN (IoT-devices) has a few difficulties such as energy and bandwidth consumption, and data storage issues resulting from frequent interactions and transactions between devices. Because these challenges cannot be resolved by one solution, we focused on reducing the energy consumption associated with a WSN. We proposed software-defined networking (SDN) model to tackle energy-efficiency issue in a WSN setup by integrating SDN and WSN, which gave rise to a more robust system, software-defined wireless sensor network (SDWSN). In this direction, we proposed an improved fuzzy-logic-based strategy, fuzzy topology discovery protocol (FTDP). It used IT-SDN (an SDN-based WSN framework) to increase the network’s lifepan due to its low energy consumption. The link layer discovery protocol (LLDP) to build the SDN controller’s topology. The system’s performance was presented and compared, demonstrating that with an effective SDWSN discovery policy, energy efficiency is achievable.
Extractive text summarization for scientific journal articles using long short-term memory and gated recurrent units
Authors: Fitrianah Devi , Jauhari Raihan Nugroho
Published: January 2022

Along with the increasing number of scientific publications, many scientific communities must read the entire text to get the essence of information from a journal article. This will be quite inconvenient if the scientific journal article is quite long and there are more than one journals. Motivated by this problem, encourages the need for a method of text summarization that can automatically, concisely, and accurately summarize a scientific article document. The purpose of this research is to create an extractive text summarization by doing feature engineering to extract the semantic information from the original text. Comparing the long short-term memory algorithm and gated recurrent units and were used to get the most relevant sentences to be served as a summary. The results showed that both algorithms yielded relatively similar accuracy results, with gated recurrent units at 98.40% and long short-term memory at 98.68%. The evaluation method with matrix recall-oriented understudy for gisting evaluation (ROUGE) is used to evaluate the summary results. The summary results produced by the LSTM model compared to the summary results using the latent semantic analysis (LSA) method were then obtained recall values at ROUGE-1, ROUGE-2, and ROUGE-L respectively were 76.25%, 59.49%, and 72.72%.
Design and modeling industrial intelligent robot flexible hand
Authors: Polishchuk Mikhail , Tkach Mikhail , Parkhomey Igor , Boiko Juliy , Eromenko Oleksander
Published: January 2022

The article describes a description of a fundamentally new design, mathematical model and experimental research of a flexible arm with an anthropomorphic gripper for an industrial robot. The advantage of the proposed design of the robot arm in comparison with the known traditional technical solutions is achieved as close as possible to the functions of the human arm. This property significantly increases the versatility of the robot arm when performing various technological operations. Another difference from the known models of industrial robots is the presence of an anthropomorphic gripping device in the flexible arm, which allows you to service products with different shapes and arbitrary coordinates in space. In addition, the article for the first time proposes a method for calculating the parameters of a new hand and experimental studies of its functioning, which will allow engineers in the field of robotics to create similar designs. The economic effect of the proposed design is that the implementation of the movements of the proposed robot arm does not require separate electromechanical drives for each joint of the kinematic chain of the manipulator. This effect significantly reduces the cost of a robot arm while expanding its technological capabilities.
Mapping of human arm impedance characteristics in spatial movements
Authors: Choudhury Tasnuva Tabashhum , Rahman Md Mozasser , Khan Md Raisuddin , Rashid Fazlur , Sarker Md. Rabiul Islam
Published: January 2022

In this paper, impedance characteristics are determined for discrete movement. It explores the changes in impedance characteristics of human arm during a complete task. This study considered 3D spatial movement for horizontal adduction and abduction. The human arm is considered as mass-spring-damper system and the modelling is done accordingly. The model is solved for 3 degree of freedom (3DoF) spatial movement usually used for daily work. Inertia, stiffness and damping factor are the impedance characteristics considered in the model. Using position measuring device, the position data of elbow and wrist were obtained with respect to pre-defined references. The data were used to calculate velocity, acceleration and force. Then, the impedance characteristics were determined by solving the equation of motion of the mass-spring-damper system corresponding to different position of the wrist on the trajectory. These impedance factors were then plotted to map the characteristics. The mappings were done for both total durations to complete task and for segments of the task. The impedance characteristics were observed to vary according to the movement of the arm. Significant changes of damping factor and stiffness were found to occur at the beginning and end of the arm movement.
Distributed memory of neural networks and the problem of the intelligence`s essence
Authors: Suleimenov Ibragim E. , Matrassulova Dinara K. , Moldakhan Inabat , Vitulyova Yelizaveta S. , Kabdushev Sherniyaz B. , Bakirov Akhat S.
Published: January 2022

The question of the nature of the distributed memory of neural networks is considered. Since the memory capacity of a neural network depends on the presence of feedback in its structure this question requires further study. It is shown that the neural networks without feedbacks can be exhaustively described based on analogy with the algorithms of noiseproof coding. For such networks the use of the term "memory" is not justified at all. Moreover, functioning of such networks obeys the analog of Shannon formula, first obtained in this paper. This formula allows to specify in advance the number of images that a neural network can recognize for a given code distance between them. It is shown that in the case of artificial neural networks with negative feedback it is really justified to talk about a distributed memory network. It is also shown that in this case the boundary between distributed memory of a neural network and information storage mechanisms in such elements as RS-triggers is diffuse. For the given example a specific formula is obtained, which connects the number of possible states of outputs of the network (and, hence, the capacity of its memory) with the number of its elements.
Inspection based risk management of electric distribution overhead lines
Authors: Tawafan Adnan Hasan , Alshadood Dhafer Mayoof , Abd Fatima Kadhem
Published: January 2022

This paper introduces a comprehensive process based on inspection for determination of medium voltage (MV) overhead line condition and it was tried that all factors influencing the outage of distribution network integrated into one index that called condition index. A condition based failure rate model has been proposed and its unknown parameters are calculated based on historical data. Shortest path problem (SPP) model has been proposed for the long term scheduling of maintenance and reinvestment. Objective function includes sum of the reinvestment, maintenance costs, failure costs and energy not supplied (ENS) costs with considering budget and labor constraints. Finally, as a result of this research, optimal combination of various actions such as reinvestment, preventive maintenance (PM) and tree trimming and it’s scheduling has been determined over the ten and five-year horizon. Results confirmed acceptable performance of proposed method because of compliance with actual condition and engineering judgment.
Artificial speech detection using image-based features and random forest classifier
Authors: Tan Choon Beng , Ahmad Hijazi Mohd Hanafi , Kok Frazier , Mohamad Mohd Saberi , Ellyza Nohuddin Puteri Nor
Published: January 2022

The ASVspoof 2015 Challenge was one of the efforts of the research community in the field of speech processing to foster the development of generalized countermeasures against spoofing attacks. However, most countermeasures submitted to the ASVspoof 2015 Challenge failed to detect the S10 attack effectively, the only attack that was generated using the waveform concatenation approach. Hence, more informative features are needed to detect previously unseen spoofing attacks. This paper presents an approach that uses data transformation techniques to engineer image-based features together with random forest classifier to detect artificial speech. The objectives are two-fold: (i) to extract image-based features from the melfrequency cepstral coefficients representation of the speech signal and (ii) to compare the performance of using the extracted features and Random Forest to determine the authenticity of voices with the existing approaches. An audio-to-image transformation technique was used to engineer new features in classifying genuine and spoof voices. An experiment was conducted to find the appropriate combination of the engineered features and classifier. Experimental results showed that the proposed approach was able to detect speech synthesis and voice conversion attacks effectively, with an equal error rate of 0.10% and accuracy of 99.93%.
Limitações na comparação dos Inquéritos Nacionais de Alimentação de 2008–2009 e 2017–2018
Authors: Rodrigues Renata Muniz , De Carli Eduardo , Araújo Marina Campos , Junior Eliseu Verly , Marchioni Dirce Maria Lobo , Bezerra Ilana Nogueira , Souza Amanda de Moura , Yokoo Edna Massae , Pereira Rosangela Alves , Sichieri Rosely
Published: January 2022

OBJETIVO: Apresentar particularidades dos dois Inquéritos Nacionais de Alimentação (INA) e o processo metodológico empregado para comparação dos dados. MÉTODOS: O estudo detalha as diferenças entre os INA realizados pelo IBGE em 2008–2009 e em 2017–2018, apresentando as alterações nos métodos de coleta de dados e nas tabelas de composição dos alimentos, assim como as estratégias de análise recomendadas para comparação dos dados. Um estudo de validação foi realizado com 95 participantes da terceira onda do Estudo Longitudinal de Saúde do Adulto a fim de avaliar o erro de medição associado aos procedimentos adotados nos recordatórios de 24 horas do INA 2017–2018. Empregaram-se biomarcadores de recuperação urinária de proteínas, sódio e potássio como padrões de referência. Na análise dos INA, diferentes estratégias foram elaboradas para comparar dois itens importantes do consumo alimentar que sofreram mudanças na forma de coleta: as gorduras e os açúcares. RESULTADOS: O estudo de validação do instrumento indicou menor sub-relato no inquérito mais recente, com maiores médias de ingestão de energia. A correlação das medidas dos recordatórios de 24 horas com os respectivos biomarcadores foi de 0,58 para proteínas, 0,31 para potássio e 0,30 para sódio. Comparando as tabelas de composição utilizadas nos dois inquéritos com os dados obtidos no INA 2008–2009, a variação média de energia, macronutrientes e minerais foi menor que 15%, com exceção das gorduras trans e selênio, com médias 40% e 52% menores na TBCA. No INA 2017–2018, as médias do consumo de açúcar de adição foram menores, usando a informação do açúcar reportado como item de adição comparada com a pergunta genérica sobre a frequência do uso do açúcar. CONCLUSÃO: As mudanças metodológicas incluídas no INA atual permitiram aprimorar as estimativas de consumo de grupos de alimentos e nutrientes, acrescentando informações mais detalhadas e específicas aos relatos do consumo alimentar.
The Influence of Gentrification and Murders by Youths
Authors: Argueta Jaime R. , Liu Lin , Eck John E.
Published: January 2022

Research shows that gentrification influences crime. However, there are no quantitative studies on gentrification’s impact on juvenile offending. This paper begins to fill this gap by examining the impact of gentrification on homicides by juveniles. To do this, we use Block, Block, and Illinois Criminal Justice Information Authority’s data on Chicago Homicides from 1965 through 1995. We couple these data with historical census data to create a dataset of victims killed by juveniles within gentrified and non-gentrified census tracts. We employ a pooled, longitudinal Poisson regression model. Our findings indicate that gentrification is moderately and negatively associated with people killed by juveniles.
Feeling at Home in Two Cultural Worlds: Bicultural Identity Integration Moderates Felt Authenticity
Authors: Mok Aurelia
Published: January 2022

Bicultural individuals navigate and identify with two cultures. Biculturals differ in levels of Bicultural Identity Integration (BII)—how much their two cultural identities are combined and compatible (high BII) versus divided and conflicting (low BII). We hypothesized that during conformity in cultural ingroup contexts, biculturals with low BII feel inauthentic (being untrue to themselves), whereas biculturals with high BII feel authentic (being true to themselves). Across four experiments with Asian-Americans, expressing cultural conformity (vs. non-conformity) in Asian or American contexts produced felt inauthenticity among participants with low BII but not high BII (Studies 1–3). Felt inauthenticity was due to cultural identity threat (perceived identity exclusion) (Study 2). Activating self-kindness counteracted felt inauthenticity for low BII participants during cultural conformity (Study 3) and produced felt authenticity (Study 4). Our findings imply that responding kindly to the self makes biculturals at ease in their cultural homes, at least temporarily.
Early-life mice housed in standard stocking density reduce the spontaneous physical activity and increase visceral fat deposition before reaching adulthood
Authors: Scariot Pedro PM , Gobatto Claudio A , Polisel Emanuel EC , Gomes Ana EC , Beck Wladimir R , Manchado-Gobatto Fúlvia B
Published: January 2022

Laboratory rodents spend the entire day housed in standard cages that provide a restricted area for movements and might, therefore, limit physical activity. However, it has not been tested in immature rodents of ages ranging from weaning to adulthood (adolescence period) whether the restricted area per animal does actually reduce physical activity and impact the body composition. We analyzed the spontaneous physical activity and feeding behavior during the adolescence of mice kept in two different housing conditions (standard stocking density (SSD) versus low stocking density (LSD)). We aimed to compare the body composition between SSD and LSD groups before they reached adulthood. Differential housing began at four weeks of age and was maintained for four weeks until euthanasia at eight weeks of age. The SSD group had a floor space of 88 cm2 available per animal, while LSD mice were housed with a floor space of 320 cm2 per animal, increasing the individual radius for movement more than three-fold compared with standard requirements. Mice kept in SSD exhibit lower spontaneous physical activity than mice kept in LSD. Early-life exposure to reduced physical activity in mice housed in SSD resulted in greater visceral fat accumulation before adulthood. An environment enabling/stimulating physical activity should be established for rodents as early as possible. This study will be helpful in showing that mice kept in SSD are early exposed to a reduced physical activity already in the adolescence period. Our findings could raise reflections about the translatability of rodents kept in SSD to healthy active humans.
Guns Are Not Faster to Enter Awareness After Seeing a Black Face: Absence of Race-Priming in a Gun/Tool Task During Continuous Flash Suppression
Authors: Stein Timo , Ciorli Tommaso , Otten Marte
Published: January 2022

In the Weapon Identification Task (WIT), Black faces prime the identification of guns compared with tools. We measured race-induced changes in visual awareness of guns and tools using continuous flash suppression (CFS). Eighty-four participants, primed with Black or Asian faces, indicated the location of a gun or tool target that was temporarily rendered invisible through CFS, which provides a sensitive measure of effects on early visual processing. The same participants also completed a standard (non-CFS) WIT. We replicated the standard race-priming effect in the WIT. In the CFS task, Black and Asian primes did not affect the time guns and tools needed to enter awareness. Thus, race priming does not alter early visual processing but does change the identification of guns and tools. This confirms that race-priming originates from later post-perceptual memory- or response-related processing.
The Utility of Latent Class Analysis to Understand Heterogeneity in Youth Coping Strategies: A Methodological Introduction
Authors: Nylund-Gibson Karen , Garber Adam C. , Singh Jay , Witkow Melissa R. , Nishina Adrienne , Bellmore Amy
Published: January 2022

Latent class analysis (LCA) is a useful statistical approach for understanding heterogeneity in a population. This article provides a pedagogical introduction to LCA modeling and provides an example of its use to understand youths’ daily coping strategies. The analytic procedures are outlined for choosing the number of classes and integration of the LCA variable within a structural equation model framework, specifically a latent class moderation model, and a detailed table provides a summary of relevant modeling steps. This applied example demonstrates the modeling context when the LCA variable is moderating the association between a covariate and two outcome variables. Results indicate that students’ coping strategies moderate the association between social stress and negative mood; however, they do not moderate the social stress-positive mood association. Online supplemental materials include R (MplusAutomation) code to automate the enumeration procedure, ML three-step auxiliary variable integration, and the generation of figures for visually depicting LCA results.
COVID-19: Modeling Out-of-Home and In-Home Activity Participation during the Pandemic
Authors: Hossain Md. Shahadat , Haque Khademul , Fatmi Mahmudur Rahman
Published: January 2022

Understanding the interaction between in-home and out-of-home activity participation decisions is important, particularly at a time when opportunities for out-of-home activities such as shopping, entertainment, and so forth are limited because of the COVID-19 pandemic. The travel restrictions imposed as a result of the pandemic have had a massive impact on out-of-home activities and have changed in-home activities as well. This study investigates in-home and out-of-home activity participation during the COVID-19 pandemic. Data comes from the COVID-19 Survey for assessing Travel impact (COST), conducted from March to May in 2020. This study uses data for the Okanagan region of British Columbia, Canada to develop the following two models: a random parameter multinomial logit (RPMNL) model for out-of-home activity participation and a hazard-based random parameter duration (HRPD) model for in-home activity participation. The model results suggest that significant interactions exist between out-of-home and in-home activities. For example, a higher frequency of out-of-home work-related travel is more likely to result in a shorter duration of in-home work activities. Similarly, a longer duration of in-home leisure activities might yield a lower likelihood for recreational travel. Health care workers are more likely to engage in work-related travel and less likely to participate in personal and household maintenance activities at home. The model confirms heterogeneity among the individuals. For instance, a shorter duration of in-home online shopping yields a higher probability for participation in out-of-home shopping activity. This variable shows significant heterogeneity with a large standard deviation, which reveals that sizable variation exists for this variable.
Environmentally Tuning Asphalt Pavements Using Microencapsulated Phase Change Materials
Authors: Montoya Miguel A. , Betancourt Daniela , Rahbar-Rastegar Reyhaneh , Youngblood Jeffrey , Martinez Carlos , Haddock John E.
Published: January 2022

Environmental conditions are considered an important factor influencing asphalt pavement performance. The addition of modifiers, both to the asphalt binder and the asphalt mixture, has attracted considerable attention in potentially alleviating environmentally induced pavement performance issues. Although many solutions have been developed, and some deployed, many asphalt pavements continue to fail prematurely because of environmental loading. The research reported here investigates the inclusion of microencapsulated phase change material (μPCM) in asphalt binders and mixtures to help reduce environmental damage to asphalt pavements. The μPCM particles are formulated to absorb and release thermal energy as the particles liquify and solidify, depending on pavement temperature. As a result, μPCM can provide asphalt pavements with thermal energy storage capacities to reduce the impacts of drastic ambient temperature scenarios and minimize the appearance of critical temperatures within the pavement structure. By modifying asphalt pavement materials with μPCM, it may be possible to “tune” the pavement to the environment. Through rheology, differential scanning calorimetry, thermal cycling, and dynamic modulus testing, this work attempts to capture the μPCM effect and link the behavior between μPCM modified asphalt binders and mixtures. This study identifies a novel approach to determine when the μPCM effect occurs using rheological measurements. Additionally, the thermal and mechanical performances of μPCM modified asphalt mixtures are evaluated. An asphalt mixture design method is demonstrated to systematically incorporate a substantial portion of μPCM particles in a reference mixture. The findings extend the thermomechanical understanding of μPCM modified asphalt binders and mixtures.
Safety and Economic Evaluation of the Highway Safety Improvement Program: Is there a Return on Investment?
Authors: Claros Boris , Schroeder Erynn , Brummett Kentin , Chitturi Madhav , Bill Andrea , Noyce David A.
Published: January 2022

The Highway Safety Improvement Program (HSIP) is a Federal-aid program aimed at achieving a significant reduction in traffic fatalities and serious injuries on all public roads. Projects are selected based on the potential reduction of severe crashes and the greatest return on investment. In this paper, a step-by-step process and methodology were developed to evaluate HSIP projects. The process and method were implemented to evaluate HSIP projects executed in Wisconsin between 2013 and 2019. Safety effectiveness evaluation and economic assessment were conducted using the Empirical Bayes (EB) method. Crash cost benefit of implemented projects was quantified to find the benefit–cost (B/C) for a horizon of 10 years and observed period of analysis. With data available from project evaluations, Crash Modification Factors (CMFs) for common treatments were developed. A total of 64 HSIP projects were evaluated. B/C ratios greater than one were observed in 43 projects. For a 10-year horizon, the aggregated B/C ratio was 2.71. Alternatively, using the observed data during the study period of each project, the observed overall crash cost benefit was equal to $72 million which corresponds to a B/C ratio of 1.10 (benefit already surpassed project costs at 3–5 years). Approximately 536 crashes were prevented which translates to seven lives saved, 380 injuries prevented, and avoided 1,067 property damage losses.
Approach to Determination of Risk-Based Inspection Workload for Highway Construction Projects
Authors: Mohamed Mamdouh , Tran Daniel
Published: January 2022

State departments of transportation (DOTs) are increasingly charged with developing and managing more highway construction projects while facing a substantial challenge in performing construction inspection activities with reduced resources of funding and inspection staff. Several state DOTs have applied workload reduction approaches including risk-based inspection methods to offset the shortage of inspection resources. The purpose of this study was to develop a framework to determine an appropriate inspection workload associated with construction inspection risk levels. The framework included three stages: (1) determination of project needs of inspection workforce, (2) utilizing risk-based prioritization of inspection activities, and (3) allocation of the workforce based on risk levels of inspection activities. The proposed framework was developed based on data collected from a comprehensive literature review and survey questionnaires of 50 state DOTs. The findings from this study indicated that almost all 38 responding state DOTs have a shortage of inspection staff. Four main strategies that state DOTs used to overcome the shortage of inspection workforce include outsourcing quality assurance (QA) inspections to consultants, using contractors’ test results for acceptance, reducing the number of inspections and testing frequency, and prioritizing QA inspections. The framework was tested and calibrated with a case study project in Kansas. The result shows that the proposed framework can be implemented by state DOTs to increase the value of inspection with a limited workforce. The framework also allows project managers to better understand and allocate the available inspection resources to alleviate the risk of quality shortfall.
Using Probe-Based Speed Data and Interactive Maps for Long-Term and COVID-Era Congestion Monitoring in San Francisco
Authors: Sana Bhargava , Zhang Xu , Castiglione Joe , Chen Mei , Erhardt Gregory D.
Published: January 2022

Probe data that provide roadway speeds and travel times are increasingly being used for a variety of purposes in the transportation domain. A key use of these datasets has been roadway performance monitoring by state and local transportation agencies that are mandated to measure and report performance of their transportation networks. The San Francisco County Transportation Authority (SFCTA) monitors roadway performance as a part of the biennial Congestion Management Program (CMP) and primarily uses probe-based speed data for that purpose. Despite considerable savings in time and effort for data collection, integrating and processing the probe data still required a significant amount of manual work. This study highlights these challenges and proposes a data processing pipeline which includes an automated network conflation process, an efficient large data processing framework, and an interactive web-based visualization. In addition, all the scripts and code developed were made open source and are readily accessible from a public repository on GitHub. The value of the pipeline is demonstrated through the development of web-based interactive maps to monitor both long-term and short-term congestion in San Francisco. The short-term congestion monitoring application is timely given the spread of the COVID-19 pandemic and the region’s rapidly changing traffic conditions. Several valuable lessons learned from use of probe data for roadway performance monitoring are shared. Developing tools to ensure consistency of the data product and to reduce reliance on any one data vendor is of key importance.
Evaluation of a Continuous Laser Ablation Coating Removal Device for Steel Bridges
Authors: Provines Jason , Rickard Raquel , Sharp Stephen
Published: January 2022

One common method for removing deteriorated coatings from steel bridges is abrasive blast cleaning. Although effective, abrasive blast cleaning can be hazardous to operators and must be conducted using expensive containment. One innovative solution to the hazardous nature and high expense of blast cleaning is laser ablation coating removal (LACR). LACR uses a high-energy laser, rather than conventional blasting, to remove the coating and has the potential to minimize operator hazards and eliminate the need for containment. The purpose of this study was to evaluate a continuous LACR system in relation to its coating removal effectiveness, industrial hygiene (IH), and effect on the steel substrate below the underlying coating. Coating removal and IH evaluation were performed on coated steel samples, including some with lead and other toxic metal coatings. LACR was also performed on bare steel, used to perform mechanical testing, such as tension, fatigue, hardness, and microstructural analysis to evaluate the effect of LACR on a steel substrate. In comparison to the pulsed LACR system evaluated in a previous study, the continuous LACR system was 2–27 times faster at removing most coatings, but it was unable to remove white coatings like the pulsed LACR system was able to do. IH evaluation showed that the continuous LACR system was likely to generate toxic metal fumes when ablating lead coatings, but this could possibly be minimized by designing an attached fume extraction system. Mechanical testing showed that the continuous LACR had no detrimental effects to the steel substrate.
Quantitative Proxies for Social Norms: A Proposed Approach for Interrogating Clustering, Reference Groups, and Validity
Authors: Seff Ilana , Cislaghi Beniamino , Levtov Ruti , Vlahovicova Kristina , Stark Lindsay
Published: January 2022

A growing number of researchers studying intimate partner violence (IPV) employ aggregate measures of relevant attitudes to serve as proxy measures for norms around IPV. However, there is a lack of consistency in how these measures are constructed and how their validity is confirmed. The first aim of this study is to demonstrate and validate innovative techniques for exploring social norms proxies in quantitative data and identifying the relative appropriateness of different available reference groups. The second aim is to demonstrate how such an approach can contribute to IPV research. The analysis employed data from the 2016 Tanzania International Men and Gender Equality Survey, including 1008 men and 1008 women ages 15–49 years. An attitudinal score measuring acceptance of IPV and two measures for individual-level descriptive and injunctive norms were constructed. The intraclass correlation coefficient (ICC) was used to assess the extent of clustering for the attitudinal score within several sets of groupings. Bivariate multi-level Ordinary Least Squares regressions estimated the predictive effect of an individual’s group norm proxy on their descriptive or injunctive norms. Attitudinal clustering was most significant for reference groups defined as males only across villages and males only across a combination of villages and marital status, with ICCs of 0.229 and 0.236, respectively. Men’s social norms were found to be correlated with reference groups comprised of both men only and women only, though men’s norms were substantially more correlated with the attitudes of men in their reference group than with women’s. Results highlight the importance of critically examining the validity of proxy measures for social norms prior to their inclusion in analysis. Findings also underscore the importance of collecting attitudinal data from men to better understand norms around IPV.
A tissue-selective estrogen complex as treatment of osteoporosis in experimental lupus
Authors: Nordqvist Jauquline , Engdahl Cecilia , Scheffler Julia M , Gupta Priti , Gustafsson Karin L , Lagerquist Marie K , Carlsten Hans , Islander Ulrika
Published: January 2022

Osteoporosis is a common secondary complication in patients with systemic lupus erythematosus (SLE). Current osteoporosis treatment with bisphosphonates has some negative side effects and there is a lack of data regarding newer treatments options for SLE associated osteoporosis. The tissue-selective estrogen complex (TSEC) containing conjugated estrogens and the selective estrogen receptor modulator bazedoxifene (Bza) is approved for treatment of postmenopausal vasomotor symptoms and prevention of osteoporosis. However, it has not been evaluated for treatment of osteoporosis in postmenopausal SLE patients. Ovariectomized MRL/ lpr mice constitute a model for postmenopausal lupus that can be used for osteoporosis studies. We used this model in a set of experiments where the mice were treated with different doses of 17β-estradiol-3-benzoate (E2), Bza, or TSEC (E2 plus Bza), administered in the early or late phases of disease development. The skeleton was analyzed by dual-energy X-ray absorptiometry, peripheral quantitative computed tomography, and high-resolution microcomputed tomography. The lupus disease was assessed by determination of proteinuria, hematuria, and lupus disease markers in serum. Treatment with medium dose TSEC administered in early disease protected ovariectomized MRL/ lpr mice from trabecular bone loss, while there were no differences in lupus disease parameters between treatments. This is the first experimental study to investigate TSEC as a potential new therapy for osteoporosis in postmenopausal SLE.
State, Labour and Emerging Natural Resource Regimes: A Case Study of Forest- Based Livelihoods in Chamba, Himachal Pradesh
Authors: Krithi S.
Published: January 2022

Third world environmental policies are increasingly moving towards market-based mechanisms for conservation of natural resources. In India, the Compensatory Afforestation Fund Act, a key element of current policy on forest restoration, reflects this shift. While it has not been explicitly formulated as payment for ecosystem services, this policy relies on the use of market-based valuation techniques to finance equivalent afforestation for diverted forest land by the state. Using a mix of government reports, secondary data and primary survey, this article studies the manifestation of conservation in a hilly, forested and remote region within India and its implications on sustainability and equity for local resource users. The primary data shows the continuing process of encroachment of the commons, commodification and devaluation of natural resources at the local level. Simultaneously, a re-articulated notion of conservation is being used to bring the natural resource sector within the ambit of capital. This article examines the shift in forest policy in Himachal Pradesh, India, the changing relationship of state, local institutions and private investment, and how the articulation of conservation has interacted with policy and practice. As a beleaguered neoliberal capitalist system searches for avenues for profit, this article re-emphasizes the role of a democratic state and the inability of private capital to address social needs.
Trade Competition Between ASEAN, China, and India: The Post-trade War and COVID-19 Scenario
Authors: Kato Atsuyuki
Published: January 2022

This study examines the exports of large developing economies; such as Association of South-East Asian Nations (ASEAN), China, and India, and discusses the post-trade war and COVID-19 scenario. Applying an export sophistication index to their trade data, we investigate the export structure of these economies. In addition, using regression analysis, we examine the resilience of their skill and technology-intensive manufacturing exports to exchange rate and demand shocks. The estimated export sophistication index detects that China’s export sophistication has not always been a step ahead in comparison to ASEAN countries and India, which contrasts with China’s remarkable export growth. Our panel DOLS estimation reveals that their manufacturing exports are highly responsive to demand shocks, although the effects of bilateral exchange rate changes vary across product groups. An appreciation of the competitors’ currencies possibly encourages their manufacturing exports. In addition, our estimation reveals that China possibly mitigates the negative effects of the trade war and COVID-19 with its advantage in the global value chains as a contributor of value-added. These results have some implications for the effects of decoupling China and the USA because of their trade war and COVID-19 situation.
Utilization of the Healthy Indonesia Program With a Family Approach Data During the COVID-19 Pandemic
Authors: Sulistiowati Eva , Yunianto Andre , Yanti Fifi
Published: January 2022

The public health center conducted the Healthy Indonesia Program With a Family Approach (HIPFA) in their working area and had family and personal data. It can be used as a priority target for efforts to cut the COVID-19 transmission chain. The aim was to describe HIPFA data’s utilization in mapping the vulnerable groups, monitoring cases during the COVID-19 pandemic, and analyzing the obstacles faced. This analysis uses secondary data of HIPFA and patient visits at Kalibawang Public Health Center Kulonprogo. The result shows that HIPFA data were useful in mapping the vulnerable age groups and comorbidity. The data can be presented by personal and village areas. The output of merging HIPFA and patients’ visit data confirmed by COVID-19 shows that there are household members who have children below 5 years old and hypertension. Data can use as a basis for COVID-19 case management. The obstacles of the analysis like the Healthy Family application have not shown updated data longitudinally; using National Identity Number (NIN) was not uniform in program reporting, limitation of human resource capabilities to analyze data. The HIPFA data were useful in mapping the vulnerable groups to prevent transmission and COVID-19 case management.