bluuebunny/crossref_metadata_2025 huggingface dataset:
Multitarget Search Algorithm Using Swarm Robots in an Unknown 3D Mountain Environment
Authors: Zhou You , Zhou Shaowu , Wang Mao , Chen Anhua
Published: February 2023

A multitarget search algorithm for swarm robot in an unknown 3D mountain environment is proposed. Most existing 3D environment obstacle avoidance algorithms are potential field methods, which need to consider the location information of all obstacles around the robot, and they easily fall into local optima, and their calculation is complex. Furthermore, they cannot well meet the requirements of real-time obstacle avoidance characteristics of swarm robots in multiobject searches. This paper first focuses on solving the obstacle avoidance problem of swarm robots in mountain environments. A new 3D curved obstacle tracking algorithm (3D-COTA) is designed by discretizing the mountains within the detection range of robot obstacles. Then, a task assignment model and virtual force model in 2D space are extended to 3D, and a particle swarm search model with kinematic constraints is constructed, which considers the kinematic constraints and the limitations of the communication ability of the robots. Finally, a new multitarget search algorithm for swarm robot in an unknown 3D mountain environment is proposed by means of the designed 3D surface obstacle tracking algorithm. Numerical simulation results demonstrate the effectiveness of the proposed algorithm.
Features Engineering to Differentiate between Malware and Legitimate Software
Authors: Daeef Ammar Yahya , Al-Naji Ali , Nahar Ali K. , Chahl Javaan
Published: February 2023

Malware is the primary attack vector against the modern enterprise. Therefore, it is crucial for businesses to exclude malware from their computer systems. The most responsive solution to this issue would operate in real time at the edge of the IT system using artificial intelligence. However, a lightweight solution is crucial at the edge because these options are restricted by the lack of available memory and processing power. The best contender to offer such a solution is application programming interface (API) calls. However, creating API call characteristics that offer a high malware detection rate with quick execution is a significant challenge. This work uses visualisation analysis and Jaccard similarity to uncover the hidden patterns produced by different API calls in order to accomplish this goal. This study also compared neural networks which use long sequences of API calls with shallow machine learning classifiers. Three classifiers are used: support vector machine (SVM), k-nearest neighbourhood (KNN), and random forest (RF). The benchmark data set comprises 43,876 examples of API call sequences, divided into two categories: malware and legitimate. The results showed that RF performed similarly to long short-term memory (LSTM) and deep graph convolutional neural networks (DGCNNs). They also suggest the potential for performing inference on edge devices in a real-time setting.
The Impact of a Novel Neuromuscular Training Program on Leg Stiffness, Reactive Strength, and Landing Biomechanics in Amateur Female Rugby Players
Authors: Sikora Ondřej , Lehnert Michal , Hanzlíková Ivana , Hughes Jonathan
Published: February 2023

This randomized control study aimed to assess 12 weeks of a novel neuromuscular training program (KneeRugbyWomen) on jump-related biomechanical variables in amateur female rugby players. Twenty-four participants were randomly allocated to either an experimental group (EG; n = 12, age: 20.05 ± 4.43 yrs., height: 166.54 ± 4.46 cm, weight: 64.65 ± 6.44 kg) or a control group (CG; n = 12, age: 20.04 ± 4.88 yrs., height: 166.83 ± 7.30 cm, weight: 69.83 ± 12.84 kg). Participants were tested before and after a 12-week intervention for jump-related biomechanical variables (leg stiffness, Reactive Strength Index (RSI), and landing mechanics using the Landing Error Scoring System (LESS)). A significant increase in RSI was found in EG (p = 0.012, r = 0.70, large effect). At post-testing, players in EG had significantly greater RSI scores compared to CG at post-intervention (p = 0.007, r = 0.55, large effect). LESS scores of CG were significantly greater compared to EG at pre-intervention (p = 0.008, r = 0.55, large effect) and post-intervention (p = 0.003, r = 0.60, large effect). Results of this study demonstrate a positive effect of the KneeRugbyWomen training program on RSI, which has been previously associated with increased ACL injury risk in female players.
Optimizing Electric Taxi Battery Swapping Stations Featuring Modular Battery Swapping: A Data-Driven Approach
Authors: Liu Zhengke , Ma Xiaolei , Liu Xiaohan , Correia Gonçalo Homem de Almeida , Shi Ruifeng , Shang Wenlong
Published: February 2023

Optimizing battery swapping station (BSS) configuration is essential to enhance BSS’s energy savings and economic feasibility, thereby facilitating energy refueling efficiency of electric taxis (ETs). This study proposes a novel modular battery swapping mode (BSM) that allows ET drivers to choose the number of battery blocks to rent according to their driving range requirements and habits, improving BSS’s economic profitability and operational flexibility. We further develop a data-driven approach to optimizing the configuration of modular BSS considering the scheduling of battery charging at the operating stage under a scenario of time-of-use (ToU) price. We use the travel patterns of taxis extracted from the GPS trajectory data on 12,643 actual taxis in Beijing, China. Finally, we test the effectiveness and performance of our data-driven model and modular BSM in a numerical experiment with traditional BSM as the benchmark. Results show that the BSS with modular BSM can save 38% on the investment cost of purchasing ET battery blocks and is better able to respond to the ToU price than to the benchmark. The results of the sensitivity analysis suggest that when the peak electricity price is too high, additional battery blocks must be purchased to avoid charging during those peak periods.
A Trajectory Generation Algorithm for a Re-Entry Gliding Vehicle Based on Convex Optimization in the Flight Range Domain and Distributed Grid Points Adjustment
Authors: Li Mingjie , Zhou Chijun , Shao Lei , Lei Humin , Luo Changxin
Published: February 2023

Optimal trajectory generation for the guidance of re-entry glide vehicles is of great significance. To realize a faster generation speed and consistency with the guidance mechanism, an improved convex optimization trajectory generation algorithm based on the flight range domain for the re-entry glide vehicles is proposed in this paper. Firstly, according to the definition of the range-to-go, the projected range-to-go of the re-entry glide vehicle is presented when the dynamic model is converted to the flight range domain. Then, the attack angle and bank angle are expanded to the state variables and the change rate, which is designed as a new control variable. When the dynamic models and constraints are convexificated and discretized, the vehicle trajectory discrete convex model in the flight range domain is proposed. In order to further improve the generation speed and accuracy, an initial trajectory generation method that is close to the guidance requirements is proposed by the landing points of different control laws. In addition, by analyzing the nonlinear illegal degree of grid points, the probability density of grid points and the adjustment strategy of grid points are proposed. Finally, the ablation experiment shows that the initial trajectory generation and distributed grid points method works. With different target points, different no-fly zones, different initial states, and the Monte Carlo experiment, our method can effectively and robustly complete the generation. The lateral and longitudinal generation error is less than 1 km. And compared with the Gaussian pseudo-spectral method, our method obtained comparable accuracy and faster speed.
A Meta-Analysis on Dual Protocols for Chronic Stroke Motor Recovery: Robotic Training and tDCS
Authors: Kim Rye-Kyeong , Kang Nyeonju , Desai Zeel , Cauraugh James H.
Published: February 2023

Two popular chronic stroke rehabilitation protocols are robotic-assisted movements and transcranial direct current stimulation (tDCS). Separately, both protocols have produced encouraging motor recovery improvements. An intriguing question remains: what happens to motor recovery when both protocols are administered together? Do the two protocols together produce additive dual effects? This systematic review and meta-analysis investigated the dual effect of combining robotic training and tDCS. We investigated the potential effects of tDCS protocols in addition to robotic-training programs on motor recovery of the upper and lower extremities post-stroke. A systematic literature search identified 20 qualified studies that used robotic training combined with tDCS protocols for upper limb (i.e., 15 studies) and lower limb (i.e., 5 studies) post-stroke rehabilitation. Individuals in the subacute and chronic stages of recovery were investigated. The 20 included studies compared additive effects of the combined protocols with robotic training sham control groups. Further, we estimated short-term and long-term treatment effects of the combined protocols. The random-effects model meta-analyses failed to find any significant short-term and long-term motor improvements in the upper extremities after the combined treatments. However, robotic-assisted movements combined with tDCS protocols revealed significant moderate transient and sustained improvements in functions of the lower limbs post-stroke. These meta-analytic findings suggest clinical implications concerning coupled top-down and bottom-up training protocols (i.e., robotic training and tDCS combined), which will allow us to make progress toward post-stroke motor recovery.
LGViT: A Local and Global Vision Transformer with Dynamic Contextual Position Bias Using Overlapping Windows
Authors: Zhou Qian , Zou Hua , Wu Huanhuan
Published: February 2023

Vision Transformers (ViTs) have shown their superiority in various visual tasks for the capability of self-attention mechanisms to model long-range dependencies. Some recent works try to reduce the high cost of vision transformers by limiting the self-attention module in a local window. As a price, the adopted window-based self-attention also reduces the ability to capture the long-range dependencies compared with the original self-attention in transformers. In this paper, we propose a Local and Global Vision Transformer (LGViT) that incorporates overlapping windows and multi-scale dilated pooling to robust the self-attention locally and globally. Our proposed self-attention mechanism is composed of a local self-attention module (LSA) and a global self-attention module (GSA), which are performed on overlapping windows partitioned from the input image. In LSA, the key and value sets are expanded by the surroundings of windows to increase the receptive field. For GSA, the key and value sets are expanded by multi-scale dilated pooling to promote global interactions. Moreover, a dynamic contextual positional encoding module is exploited to add positional information more efficiently and flexibly. We conduct extensive experiments on various visual tasks and the experimental results strongly demonstrate the outperformance of our proposed LGViT to state-of-the-art approaches.
A Non-Extensive Statistical Physics View of the Temporal Properties of the Recent Aftershock Sequences of Strong Earthquakes in Greece
Authors: Avgerinou Sophia-Ekaterini , Anyfadi Eleni-Apostolia , Michas Georgios , Vallianatos Filippos
Published: February 2023

Greece is one of Europe’s most seismically active areas. Seismic activity in Greece has been characterized by a series of strong earthquakes with magnitudes up to Mw = 7.0 over the last five years. In this article we focus on these strong events, namely the Mw6.0 Arkalochori (27 September 2021), the Mw6.3 Elassona (3 March 2021), the Mw7.0 Samos (30 October 2020), the Mw5.1 Parnitha (19 July 2019), the Mw6.6 Zakynthos (25 October 2018), the Mw6.5 Kos (20 July 2017) and the Mw6.1 Mytilene (12 June 2017) earthquakes. Based on the probability distributions of interevent times between the successive aftershock events, we investigate the temporal evolution of their aftershock sequences. We use a statistical mechanics model developed in the framework of Non-Extensive Statistical Physics (NESP) to approach the observed distributions. NESP provides a strictly necessary generalization of Boltzmann–Gibbs statistical mechanics for complex systems with memory effects, (multi)fractal geometries, and long-range interactions. We show how the NESP applicable to the temporal evolution of recent aftershock sequences in Greece, as well as the existence of a crossover behavior from power-law (q ≠ 1) to exponential (q = 1) scaling for longer interevent times. The observed behavior is further discussed in terms of superstatistics. In this way a stochastic mechanism with memory effects that can produce the observed scaling behavior is demonstrated. To conclude, seismic activity in Greece presents a series of significant earthquakes over the last five years. We focus on strong earthquakes, and we study the temporal evolution of aftershock sequences of them using a statistical mechanics model. The non-extensive parameter q related with the interevent times distribution varies between 1.62 and 1.71, which suggests a system with about one degree of freedom.
Lean Manufacturing Soft Sensors for Automotive Industries
Authors: Sekhar Ravi , Solke Nitin , Shah Pritesh
Published: February 2023

Lean and flexible manufacturing is a matter of necessity for the automotive industries today. Rising consumer expectations, higher raw material and processing costs, and dynamic market conditions are driving the auto sector to become smarter and agile. This paper presents a machine learning-based soft sensor approach for identification and prediction of lean manufacturing (LM) levels of auto industries based on their performances over multifarious flexibilities such as volume flexibility, routing flexibility, product flexibility, labour flexibility, machine flexibility, and material handling. This study was based on a database of lean manufacturing and associated flexibilities collected from 46 auto component enterprises located in the Pune region of Maharashtra State, India. As many as 29 different machine learning models belonging to seven architectures were explored to develop lean manufacturing soft sensors. These soft sensors were trained to classify the auto firms into high, medium or low levels of lean manufacturing based on their manufacturing flexibilities. The seven machine learning architectures included Decision Trees, Discriminants, Naive Bayes, Support Vector Machine (SVM), K-nearest neighbour (KNN), Ensembles, and Neural Networks (NN). The performances of all models were compared on the basis of their respective training, validation, testing accuracies, and computation timespans. Primary results indicate that the neural network architectures provided the best lean manufacturing predictions, followed by Trees, SVM, Ensembles, KNN, Naive Bayes, and Discriminants. The trilayered neural network architecture attained the highest testing prediction accuracy of 80%. The fine, medium, and coarse trees attained the testing accuracy of 60%, as did the quadratic and cubic SVMs, the wide and narrow neural networks, and the ensemble RUSBoosted trees. Remaining models obtained inferior testing accuracies. The best performing model was further analysed by scatter plots of predicted LM classes versus flexibilities, validation and testing confusion matrices, receiver operating characteristics (ROC) curves, and the parallel coordinate plot for identifying manufacturing flexibility trends for the predicted LM levels. Thus, machine learning models can be used to create effective soft sensors that can predict the level of lean manufacturing of an enterprise based on the levels of its manufacturing flexibilities.
Application of Hollow Fiber Membrane for the Separation of Carbon Dioxide from Atmospheric Air and Assessment of Its Distribution Pattern in a Greenhouse
Authors: Kim Na Eun , Basak Jayanta Kumar , Kim Hyeon Tae
Published: February 2023

Research on carbon management is fueled by the growing concern over rising carbon dioxide (CO2) levels in the atmospheric air and its possible impacts on the climate. In this study, we proposed a method of CO2 separation from atmospheric air. This study aimed to investigate the effects of CO2 enrichment on the air temperature inside a greenhouse using a hollow fiber (HF) membrane system. The experiment was conducted over a period of 30 days in two experimental conditions: 15 days without CO2 enrichment (WCS) and 15 days with CO2 enrichment (CS). Results showed that the mean CO2 concentration and air temperature were highest inside the greenhouse during the CS period, with values of 1120 ppm and 37.42 °C, respectively. Regression analysis revealed a positive correlation between CO2 concentration and temperature during the CS period (R2 = 0.628). The HF membrane system was found to be effective in increasing both the CO2 concentration and air temperature inside the greenhouse. However, the system also has limitations, including the cost, maintenance, and suitability for all types of crops. Further experiments are needed to address these limitations and determine the optimal CO2 concentration for different kinds of crops growing in greenhouses.
Sensitive Grain-Size Components of Last Glacial Loess on Chinese Loess Plateau and Their Response to East Asian Winter Monsoon
Authors: Wang Qiansuo , Song Yougui , Duan Linqiong , Li Jinchan
Published: February 2023

Chinese loess provides the most detailed terrestrial records of paleoclimate changes. We employed the grain-size components of aeolian sediments to reconstruct the history of the East Asian winter monsoon (EAWM) on the Chinese Loess Plateau (CLP). Here, using the grain-size class vs. standard deviation method, we extracted the environmentally sensitive grain-size components of nine last glacial loess sections. The grain-size class vs. standard deviation diagrams showed two major grain-size components (fine and coarse), which varied from section to section. Material resource distances and post-depositional pedogenesis were the main factors affecting environmentally sensitive grain-size components. The coarse grain-size components of the Yulin, Baicaoyuan, Xifeng, and Luochuan sections were influenced by the transportation distance, while we attributed the fine grain-size components of the Weinan, Shaoling, Duanjiapo, and Chaona sections to pedogenesis. At the same time, the Mianchi section’s sensitive grain-size component was also coarse, and was affected by the local circulation from the nearby Yellow River terrace. Our comparison of sensitive grain-size components and EAWM revealed that the coarse grain-size components were progressively finer along with the EAWM from the northwest to the southeast on the CLP, and they can be regarded as the most suitable proxy indicator of the EAWM on the CLP.
Multimodal Approach for Characterizing the Quality of Parent–Child Interaction: A Single Synchronization Source May Not Tell the Whole Story
Authors: Horowitz-Kraus Tzipi , Gashri Carmel
Published: February 2023

The interaction between the parent and child is essential for the child’s cognitive and emotional development and sets the path for future well-being. These interactions, starting from birth, are necessary for providing the sensory stimulation the child needs in the critical time window of brain development. The characterization of parent–child interactions is traditionally performed by human decoding. This approach is considered the leading and most accurate way of characterizing the quality of these interactions. However, the development of computational tools and especially the concept of parent–child synchronization opened up an additional source of data characterizing these interactions in an objective, less human-labor manner. Such sources include brain-to-brain, voice/speech, eye contact, motor, and heart-rate synchronization. However, can a single source synchronization dataset accurately represent parent–child interaction? Will attending to the same stimulation, often resulting in a higher brain-to-brain synchronization, be considered an interactive condition? In this perspective, we will try to convey a new concept of the child–parent interaction synchronization (CHIPS) matrix, which includes the different sources of signals generated during an interaction. Such a model may assist in explaining the source of interaction alterations in the case of child/parent developmental/emotional or sensory deficits and may open up new ways of assessing interventions and changes in parent–child interactions along development. We will discuss this interaction during one of the parent–child joint activities providing opportunities for interaction, i.e., storytelling.
Computational Approaches to the Rational Design of Tubulin-Targeting Agents
Authors: Pérez-Peña Helena , Abel Anne-Catherine , Shevelev Maxim , Prota Andrea E. , Pieraccini Stefano , Horvath Dragos
Published: February 2023

Microtubules are highly dynamic polymers of α,β-tubulin dimers which play an essential role in numerous cellular processes such as cell proliferation and intracellular transport, making them an attractive target for cancer and neurodegeneration research. To date, a large number of known tubulin binders were derived from natural products, while only one was developed by rational structure-based drug design. Several of these tubulin binders show promising in vitro profiles while presenting unacceptable off-target effects when tested in patients. Therefore, there is a continuing demand for the discovery of safer and more efficient tubulin-targeting agents. Since tubulin structural data is readily available, the employment of computer-aided design techniques can be a key element to focus on the relevant chemical space and guide the design process. Due to the high diversity and quantity of structural data available, we compiled here a guide to the accessible tubulin-ligand structures. Furthermore, we review different ligand and structure-based methods recently used for the successful selection and design of new tubulin-targeting agents.
Comparative Research: Regulatory Mechanisms of Ribosomal Gene Transcription in Saccharomyces cerevisiae and Schizosaccharomyces pombe
Authors: Hirai Hayato , Ohta Kunihiro
Published: February 2023

Restricting ribosome biosynthesis and assembly in response to nutrient starvation is a universal phenomenon that enables cells to survive with limited intracellular resources. When cells experience starvation, nutrient signaling pathways, such as the target of rapamycin (TOR) and protein kinase A (PKA), become quiescent, leading to several transcription factors and histone modification enzymes cooperatively and rapidly repressing ribosomal genes. Fission yeast has factors for heterochromatin formation similar to mammalian cells, such as H3K9 methyltransferase and HP1 protein, which are absent in budding yeast. However, limited studies on heterochromatinization in ribosomal genes have been conducted on fission yeast. Herein, we shed light on and compare the regulatory mechanisms of ribosomal gene transcription in two species with the latest insights.
Viriforms—A New Category of Classifiable Virus-Derived Genetic Elements
Authors: Kuhn Jens H. , Koonin Eugene V.
Published: February 2023

The International Committee on Taxonomy of Viruses (ICTV) recently accepted viriforms as a new polyphyletic category of classifiable virus-derived genetic elements, juxtaposed to the polyphyletic virus, viroid, and satellite nucleic acid categories. Viriforms are endogenized former viruses that have been exapted by their cellular hosts to fulfill functions important for the host’s life cycle. While morphologically resembling virions, particles made by viriforms do not package the viriform genomes but instead transport host genetic material. Known viriforms are highly diverse: members of family Polydnaviriformidae (former Polydnaviridae) have thus far been found exclusively in the genomes of braconid and ichneumonid parasitoid wasps, whereas the completely unrelated gene transfer agents (GTAs) are widely distributed among prokaryotes. In addition, recent discoveries likely extend viriforms to mammalian genomes. Here, we briefly outline the properties of these viriform groups and the first accepted and proposed ICTV frameworks for viriform classification.
Assessing Meat Freshness via Nanotechnology Biosensors: Is the World Prepared for Lightning-Fast Pace Methods?
Authors: Felicia Wen Xia Ling , Rovina Kobun , ‘Aqilah Nasir Md Nur , Vonnie Joseph Merillyn , Yin Koh Wee , Huda Nurul
Published: February 2023

In the rapidly evolving field of food science, nanotechnology-based biosensors are one of the most intriguing techniques for tracking meat freshness. Purine derivatives, especially hypoxanthine and xanthine, are important signs of food going bad, especially in meat and meat products. This article compares the analytical performance parameters of traditional biosensor techniques and nanotechnology-based biosensor techniques that can be used to find purine derivatives in meat samples. In the introduction, we discussed the significance of purine metabolisms as analytes in the field of food science. Traditional methods of analysis and biosensors based on nanotechnology were also briefly explained. A comprehensive section of conventional and nanotechnology-based biosensing techniques is covered in detail, along with their analytical performance parameters (selectivity, sensitivity, linearity, and detection limit) in meat samples. Furthermore, the comparison of the methods above was thoroughly explained. In the last part, the pros and cons of the methods and the future of the nanotechnology-based biosensors that have been created are discussed.
Neuroplastic Changes in Addiction Memory—How Music Therapy and Music-Based Intervention May Reduce Craving: A Narrative Review
Authors: Pasqualitto Filippo , Panin Francesca , Maidhof Clemens , Thompson Naomi , Fachner Jörg
Published: February 2023

Recent findings indicate that Music Therapy (MT) and Music-Based Interventions (MBIs) may reduce craving symptoms in people with Substance Use Disorders (SUD). However, MT/MBIs can lead SUD clients to recall memories associated with their drug history and the corresponding strong emotions (addiction memories). Craving is a central component of SUD, possibly linked to relapse and triggered by several factors such as the recall of memories associated with the drug experience. Therefore, to address the topic of what elements can account for an improvement in craving symptoms after MT/MBIs, we conducted a narrative review that (1) describes the brain correlates of emotionally salient autobiographical memories evoked by music, (2) outlines neuroimaging and neurophysiological studies suggesting how the experience of craving may encompass the recall of emotionally filled moments, and (3) points out the role of perineuronal nets (PNNs) in addiction memory neuroplasticity. We highlight how autobiographical memory retrieval, music-evoked autobiographical memories, and craving share similar neural activations with PNNs which represent a causal element in the processing of addiction memory. We finally conclude by considering how the neuroplastic characteristics of addiction memory might represent the ground to update and/or recalibrate, within the therapy, the emotional content related to the recall.
Impact of General Practitioner Education on Acceptance of an Adjuvanted Seasonal Influenza Vaccine among Older Adults in England
Authors: de Lusignan Simon , Ashraf Mansoor , Ferreira Filipa , Tripathy Manasa , Yonova Ivelina , Rafi Imran , Kassianos George , Joy Mark
Published: February 2023

Seasonal vaccination against influenza and in-pandemic COVID-19 vaccination are top public health priorities; vaccines are the primary means of reducing infections and also controlling pressures on health systems. During the 2018–2019 influenza season, we conducted a study of the knowledge, attitudes, and behaviours of 159 general practitioners (GPs) and 189 patients aged ≥65 years in England using a combination of qualitative and quantitative approaches to document beliefs about seasonal influenza and seasonal influenza vaccine. GPs were surveyed before and after a continuing medical education (CME) module on influenza disease and vaccination with an adjuvanted trivalent influenza vaccine (aTIV) designed for patients aged ≥65 years, and patients were surveyed before and after a routine visit with a GP who participated in the CME portion of the study. The CME course was associated with significantly increased GP confidence in their ability to address patients’ questions and concerns about influenza disease and vaccination (p < 0.001). Patients reported significantly increased confidence in the effectiveness and safety of aTIV after meeting their GP. Overall, 82.2% of the study population were vaccinated against influenza (including 137 patients vaccinated during the GP visit and 15 patients who had been previously vaccinated), a rate higher than the English national average vaccine uptake of 72.0% that season. These findings support the value of GP-patient interactions to foster vaccine acceptance.
Performance Evaluation of Urban Water Environment Treatment PPP Projects Based on Cloud Model and OWA Operator
Authors: Jiao Hongbo , Cao Yongchao , Li Huimin
Published: February 2023

The public-private partnership (PPP) model has become one of the marketization models for water environment treatment projects. Evaluating the performance of these projects is vital for their long-term success. Performance evaluations can inform the government when allocating expenditures for the operation and maintenance of services and can guide the private sector’s operation and maintenance management of projects. By attending to the specific characteristics of urban water environment treatment PPP projects (UWETP-PPP), this study developed a performance evaluation system and corresponding performance evaluation model comprised of eight first-level indicators and fifty second-level indicators. This model was used to evaluate a water environment treatment and ecological restoration project located in Xuchang, China. The results generated by the performance evaluation model indicated that this project was satisfactory and used the PPP model with a very high level of success, which accurately reflected real-world assessments of the project and verified the effectiveness of the model. This research provides guidance for the government in designing a performance evaluation mechanism that implements the specific characteristics of PPP projects. It also provides practical value for the operation management and performance improvement of PPP projects in China.
Experimental Investigation on Aging and Energy Savings Evaluation of High Solar Reflective Index (SRI) Paints: A Case Study on Residential Households in the GCC Region
Authors: Nutakki Tirumala Uday Kumar , Kazim Waqar Ullah , Alamara Kadhim , Salameh Tareq , Abdelkareem Mohammad Ali
Published: February 2023

Energy-efficient retrofitting of building envelopes is necessary to reduce global carbon emissions and to reach net-zero goals. Cooling energy demand-dominated countries in the GCC region require simple and effective strategies to reduce building sector energy loads. One such approach is using high solar reflective index (SRI) paints to retrofit building roofs and walls. However, the hot and desert conditions of the region pose a barrier to maintaining consistent radiative properties throughout their life cycle. To this extent, research is limited in the region. The novelty of this work is to qualitatively assess the aging characteristics of high SRI or cool paints and estimate the energy savings for their application in residential buildings. The work encompasses comprehensive lab, pilot, and real-scale experimental studies combined with theoretical modeling for dynamic evaluation. Dynamic simulations enabled to determine the time-dependent aging effect on the energy savings performance of the building retrofitted with cool roof and wall paints. A case study on a townhouse in UAE showed annual energy savings of 34% considering cool roofs, walls, and window films. Aging studies showed SRI reduction of 36% and 25%, respectively, for cool roofs and walls during the first 3 years. The corresponding energy-saving reductions ranged from 31 to 44% for the white roof to dark wall colors. Using the initial values of SRI in energy models overestimates saving by 10% per year. Considering the aging effects, this work provides insights into cool paint retrofit potential on energy, economic savings, and CO2 reductions for four major cities in the GCC region.
A Two-Step FE Model Updating Approach for System and Damage Identification of Prestressed Bridge Girders
Authors: Malekghaini Niloofar , Ghahari Farid , Ebrahimian Hamed , Bowers Matthew , Ahlberg Eric , Taciroglu Ertugrul
Published: February 2023

This study presents a two-step FE model updating approach for health monitoring and damage identification of prestressed concrete girder bridges. To reduce the effects of modeling error in the model updating process, in the first step, modal-based model updating is used to estimate linear model parameters mainly related to the stiffness of boundary conditions and material properties. In the second step, a time-domain model updating is carried out using acceleration data to refine parameters accounting for the nonlinear response behavior of the bridge. In this step, boundary conditions are fixed at their final estimates using modal-based model updating. To prevent the convergence of updating algorithm to local solutions, the initial estimates for nonlinear material properties are selected based on the first-step model updating results. To validate the applicability of the two-step FE model updating approach, a series of forced-vibration experiments are designed and carried out on a pair of full-scale decommissioned and deteriorated prestressed bridge I-girders. In the first step, parameters related to boundary conditions, including stiffness of supports and coupling beams, as well as material properties, including initial stiffness of concrete material, are estimated. In the second step, concrete compressive strength and damping properties are updated. The final estimates of the concrete compressive strength are used to infer the extent of damage in the girders. The obtained results agree with the literature regarding the extent of reduction in concrete compressive strength in deteriorated concrete structures.
Recycled Chicken Feather Sand as a Partial Replacement for Natural Sand for Producing Eco-Friendly Mortar
Authors: Defalla Abdel Hafez Radwa , Hadzima-Nyarko Marijana , Ahmed Samir M. , Tayeh Bassam A.
Published: February 2023

In this paper, initial experiments were carried out to determine the possibility of using chicken feathers instead of sand in mortar. After earlier research suggested that chicken feathers had a high durability and resilience to degradation, chicken feathers recovered from slaughterhouses were chosen due to the significant cross-linking and strong bonding within their structure. Compared to natural sand, chicken feather sand (CFS) works as an eco-friendly resource. In this study, the chicken feather content ranged from 5% to 25% of the total volume of fine aggregates. The findings confirmed that the compressive strengths of the specimens are inversely proportional to the amount of feathers added. The specimen with 10% CFS had a compressive strength of 57.8 MPa after 28 days of curing. As the weight of CFS in the mortar increased from 1.26% to 10% of the control mixture, the workability significantly decreased. After soaking in water for 24 h, materials with higher proportions of feathers had a noticeably decreased compressive and flexural strength as well as increased water absorption and swelling. For 80% of the CFS replacement, the results are good. Additional CFS replacement tends to reduce the mortar weight.
Study of the Axial Compressive Behaviour of Cross-Shaped CFST and ST Columns with Inner Changes
Authors: Tao Zhong , Hasan Md Mehedi , Han Dongji , Qin Qiudong , Abdul Ghafar Wahab
Published: February 2023

In this study, novel cross-shaped concrete-filled steel tube (CFST) and steel tube (ST) columns were developed. CFST columns have a high load-carrying capacity and excellent performance under seismic conditions, and the construction process is fast. In order to investigate the axial load bearings and failure mechanisms, six specimens of CFST and ST columns were tested under the axial load. Three different forms of CFST were employed in this study; one was an ordinary cross-shaped CFST (OC-CFST), while the other two were executed with significant inner changes; namely, stiffeners cross-shaped CFST (SC-CFST), and multi-cell cross-shaped CFST (MC-CFST) filled with concrete. The other group has the same OC-ST, SC-ST, and MC-ST, but these test subjects were without filled concrete. Through discussion of the failure mechanism, load displacement and load strain correlations are determined. The effects of parameters on ultimate resistance, failure pattern, and ductility index were studied. The axial load-carrying performance of the cross-shaped CFST columns was 75–80% better than that of ST columns; and each ST column displayed cooperative behavior. The finite element model (FEM) was simulated, and the outcomes of the experiments were used to validate it. The load–displacement relationships were established using parametric analysis. Existing design standards were used to calculate CFST column loading capacity. Finally, mathematical formulas were improvised to determine the ultimate load of the cross-shaped CFST column.
A Scientometric Analysis Review on Agricultural Wastes Used as Building Materials
Authors: Ganasen Nakkeeran , Bahrami Alireza , Loganathan Krishnaraj
Published: February 2023

The rapid urbanization of developed countries and the difficulty in disposing of agricultural wastes have created opportunities for the construction industry to use agricultural wastes. A wide variety of agricultural waste materials are already in use with concrete as substitutes for cement and aggregates, as well as reinforcing materials. This study reviews the available literature published from 1935 to 2022 on agricultural wastes being used as building materials. The research utilizes a bibliographic approach based on the Scopus database. This article retrieves data employing the Scopus database and incorporates 671 articles based on the keywords, agricultural wastes used as building materials. The scientometric analysis is the second step, wherein the patterns of the obtained articles are investigated with various factors such as countries with the most publications, sources that have the most publications, most frequently appearing keywords, and articles with more relevant research works. A summary of the results obtained at various stages of the research is depicted in each phase. Detailed quantitative and qualitative discussions are also conducted to achieve the three main objectives: the summarization of quantitative data, discussion of the existing application, and identification of future research directions. These findings serve the future endeavor of agricultural waste-to-building materials’ incineration academic research. The scientometric review paves the way for academics from various nations to impart novel ideas and information and foster research collaboration.
Energy Cost Driven Heating Control with Reinforcement Learning
Authors: Kannari Lotta , Kantorovitch Julia , Piira Kalevi , Piippo Jouko
Published: February 2023

The current energy crisis raised concern about the lack of electricity during the wintertime, especially that consumption should be cut at peak consumption hours. For the building owners, this is visible as rising electricity prices. Availability of near real-time data on energy performance is opening new opportunities to optimize energy flexibility capabilities of buildings. This paper presents a reinforcement learning (RL)-based method to control the heating for minimizing the heating electricity cost and shifting the electricity usage away from peak demand hours. Simulations are carried out with electrically heated single-family houses. The results indicate that with RL, in the case of varying electricity prices, it is possible to save money and keep the indoor thermal comfort at an appropriate level.
State of the Art MR Imaging for Lung Cancer TNM Stage Evaluation
Authors: Ohno Yoshiharu , Ozawa Yoshiyuki , Koyama Hisanobu , Yoshikawa Takeshi , Takenaka Daisuke , Nagata Hiroyuki , Ueda Takahiro , Ikeda Hirotaka , Toyama Hiroshi
Published: February 2023

Since the Radiology Diagnostic Oncology Group (RDOG) report had been published in 1991, magnetic resonance (MR) imaging had limited clinical availability for thoracic malignancy, as well as pulmonary diseases. However, technical advancements in MR systems, such as sequence and reconstruction methods, and adjustments in the clinical protocol for gadolinium contrast media administration have provided fruitful results and validated the utility of MR imaging (MRI) for lung cancer evaluations. These techniques include: (1) contrast-enhanced MR angiography for T-factor evaluation, (2) short-time inversion recovery turbo spin-echo sequences as well as diffusion-weighted imaging (DWI) for N-factor assessment, and (3) whole-body MRI with and without DWI and with positron emission tomography fused with MRI for M-factor or TNM stage evaluation as well as for postoperative recurrence assessment of lung cancer or other thoracic tumors using 1.5 tesla (T) or 3T systems. According to these fruitful results, the Fleischner Society has changed its position to approve of MRI for lung or thoracic diseases. The purpose of this review is to analyze recent advances in lung MRI with a particular focus on lung cancer evaluation, clinical staging, and recurrence assessment evaluation.
Three-Dimensional Amide Proton Transfer-Weighted Imaging for Differentiating between Glioblastoma, IDH-Wildtype and Primary Central Nervous System Lymphoma
Authors: Ohba Shigeo , Murayama Kazuhiro , Teranishi Takao , Kumon Masanobu , Nakae Shunsuke , Yui Masao , Yamamoto Kaori , Yamada Seiji , Abe Masato , Hasegawa Mitsuhiro , Hirose Yuichi
Published: February 2023

Distinguishing primary central nervous system lymphoma (PCNSL) from glioblastoma, isocitrate dehydrogenase (IDH)-wildtype is sometimes hard. Because the role of operation on them varies, accurate preoperative diagnosis is crucial. In this study, we evaluated whether a specific kind of chemical exchange saturation transfer imaging, i.e., amide proton transfer-weighted (APTw) imaging, was useful to distinguish PCNSL from glioblastoma, IDH-wildtype. A total of 14 PCNSL and 27 glioblastoma, IDH-wildtype cases were evaluated. There was no significant difference in the mean APTw signal values between the two groups. However, the percentile values from the 1st percentile to the 20th percentile APTw signals and the width1–100 APTw signals significantly differed. The highest area under the curve was 0.796, which was obtained from the width1–100 APTw signal values. The sensitivity and specificity values were 64.3% and 88.9%, respectively. APTw imaging was useful to distinguish PCNSL from glioblastoma, IDH-wildtype. To avoid unnecessary aggressive surgical resection, APTw imaging is recommended for cases in which PCNSL is one of the differential diagnoses.
Carfilzomib-Based Regimen and Cardiotoxicity in Multiple Myeloma: Incidence of Cardiovascular Events and Organ Damage in Carfilzomib-Dexamethasone versus Carfilzomib-Lenalidomide-Dexamethasone. A Real-Life Prospective Study
Authors: Astarita Anna , Mingrone Giulia , Airale Lorenzo , Cesareo Marco , Colomba Anna , Catarinella Cinzia , Leone Dario , Gay Francesca , Bringhen Sara , Veglio Franco , Milan Alberto , Vallelonga Fabrizio
Published: February 2023

Carfilzomib-mediated cardiotoxicity in multiple myeloma (MM) is a well-established adverse effect, however limited data are available on the comparison of cardiovascular complications in patients treated with Carfilzomib-dexamethasone (target dose of K 56 mg/m2) versus Carfilzomib-lenalidomide-dexamethasone (target dose of K 27 mg/m2) beyond controlled trials. A total of 109 patients were enrolled, 47 (43%) received Kd and 62 (57%) KRd. They then underwent a baseline and follow-up evaluation including trans-thoracic echocardiography and arterial stiffness estimation. All types of cardiovascular and hypertensive events occurred more frequently in the Kd group compared with the KRd (59% vs. 40% and 55% vs. 35.5% patients, respectively, p ≤ 0.05), with higher incidence of hypertensive. The time of onset of any type of CVAE, and of major and hypertensive events was shorter in the Kd regimen (p ≤ 0.05). At follow-up, Kd patients more frequently developed signs of cardiac (decline of global longitudinal strain) and vascular organ damage (rise of pulse wave velocity), as compared with KRd. Despite the older age, longer history of MM and longer period of pre-treatment of Kd patients, these factors did not increase the probability of incidence for all types of cardiovascular events at multivariate analysis (p > 0.05). In conclusion, the Kd regimen showed greater cardiovascular toxicity and earlier onset of events with respect to KRd. Thus, a closer and thorough follow-up should be considered.
Fear of Cancer Recurrence in Patients with Sarcoma in the United Kingdom
Authors: Petrella Anika , Storey Lesley , Hulbert-Williams Nicholas J. , Fern Lorna A. , Lawal Maria , Gerrand Craig , Windsor Rachael , Woodford Julie , Bradley Jennie , O’Sullivan Hatty , Wells Mary , Taylor Rachel M.
Published: February 2023

Fear of cancer recurrence (FCR) is a persistent concern among those living with cancer and is associated with a variety of negative psychosocial outcomes. However, people with sarcoma have been underrepresented within this area of research. We aimed to determine the prevalence of FCR experienced by people with sarcoma in the United Kingdom and explore factors that may predict FCR, such as the perceived impact of cancer and psychological flexibility. Participants (n = 229) with soft tissue (n = 167), bone (n = 25), and gastrointestinal stromal tumours (n = 33) completed an online survey including the self-reported measures of FCR, the perceived physical and psychological impact of cancer and psychological flexibility, and demographic information. Data were analysed using ANOVA and multiple regression modelling. Mean FCR scores (M = 91.4; SD = 26.5) were higher than those reported in meta-analytic data inclusive of all cancer types (M = 65.2; SD = 28.2). Interest in receiving support for FCR was also high (70%). Significant factors associated with FCR included cognitive and emotional distress and psychological flexibility, but not perceptions of the physical impact of cancer (R2 = 0.56). The negative association between psychological flexibility and FCR suggests the potential benefit of intervention approaches which foster psychological flexibility, such as acceptance and commitment therapy.