bluuebunny/crossref_metadata_2025 huggingface dataset:
Current Therapeutic Strategies for Metastatic Triple-Negative Breast Cancer: From Pharmacists’ Perspective
Authors: Li Shuanghe , Bao Chongyang , Huang Lingli , Wei Ji-Fu
Published: October 2022

Triple-negative breast cancer (TNBC) is characterized by its high invasiveness, high metastasis and poor prognosis. More than one-third of patients with TNBC will present with recurrence or distant metastasis. Chemotherapy based on anthracyclines and taxanes is the standard treatment strategy for metastatic TNBC (mTNBC). Due to the lack of expression of progesterone receptor, estrogen receptor, and human epidermal growth factor receptor 2, therapies targeting these receptors are ineffective for mTNBC, thus special treatment strategies are required. In recent years, the development of new chemotherapy drugs, targeted drugs and immunotherapy drugs offers good prospects for the treatment of mTNBC. However, as these drugs are still in their infancy, several problems regarding the optimization and management of the clinical application of these new options should be considered. Pharmacists can play an important role in drug selection, drug therapy management, the management of adverse drug reactions and pharmacoeconomic evaluation. In this review, we summarized traditional treatment strategies, and discussed the efficacy and safety of novel agents approved in the last ten years and combination regimens for mTNBC, with the aim of providing management strategies for the clinical management of mTNBC from pharmacists’ perspective.
The Role of Brain-Derived Neurotrophic Factor in Immune-Related Diseases: A Narrative Review
Authors: Sochal Marcin , Ditmer Marta , Gabryelska Agata , Białasiewicz Piotr
Published: October 2022

Brain-derived neurotrophic factor (BDNF) is a neurotrophin regulating synaptic plasticity, neuronal excitability, and nociception. It seems to be one of the key molecules in interactions between the central nervous system and immune-related diseases, i.e., diseases with an inflammatory background of unknown etiology, such as inflammatory bowel diseases or rheumatoid arthritis. Studies show that BDNF levels might change in the tissues and serum of patients during the course of these conditions, e.g., affecting cell survival and modulating pain severity and signaling pathways involving different neurotransmitters. Immune-related conditions often feature psychiatric comorbidities, such as sleep disorders (e.g., insomnia) and symptoms of depression/anxiety; BDNF may be related as well to them as it seems to exert an influence on sleep structure; studies also show that patients with psychiatric disorders have decreased BDNF levels, which increase after treatment. BDNF also has a vital role in nociception, particularly in chronic pain, hyperalgesia, and allodynia, participating in the formation of central hypersensitization. In this review, we summarize the current knowledge on BDNF’s function in immune-related diseases, sleep, and pain. We also discuss how BDNF is affected by treatment and what consequences these changes might have beyond the nervous system.
Learning and Transfer in Problem Solving Progressions
Authors: Daniels Jonathan S. , Moreau David , Macnamara Brooke N.
Published: October 2022

Do individuals learn more effectively when given progressive or variable problem-solving experience, relative to consistent problem-solving experience? We investigated this question using a Rubik’s Cube paradigm. Participants were randomly assigned to a progression-order condition, where they practiced solving three progressively more difficult Rubik’s Cubes (i.e., 2 × 2 × 2 to 3 × 3 × 3 to 4 × 4 × 4), a variable-order condition, where they practiced solving three Rubik’s Cubes of varying difficulty (e.g., 3 × 3 × 3 to 2 × 2 × 2 to 4 × 4 × 4), or a consistent-order condition, where they consistently practiced on three 5 × 5 × 5 Rubik’s Cubes. All the participants then attempted a 5 × 5 × 5 Rubik’s Cube test. We tested whether variable training is as effective as progressive training for near transfer of spatial skills and whether progressive training is superior to consistent training. We found no significant differences in performance across conditions. Participants’ fluid reasoning predicted 5 × 5 × 5 Rubik’s Cube test performance regardless of training condition.
Social Identity Dimensions as Drivers of Consumer Engagement in Social Media Sports Club
Authors: Marčinko Trkulja Željka , Dlačić Jasmina , Primorac Dinko
Published: October 2022

Consumer engagement is defined as a multidimensional concept in this study via the identification of members of a sports club social network and consumer identification with a sports club brand on social networks. Hence, the study focuses on sports clubs that engage with their customers through social media. The purpose of this paper is to provide a conceptual and theoretical understanding of consumer engagement, particularly among sports teams that employ interactive platforms to establish relationships with customers. Furthermore, in order to better comprehend the interaction between consumer and brand, this research approaches customer identification as consisted of two distinct constructs. Consumer identification with members of a sports club social network is separated from customer identification with a sports club brand. Research results point out that the consumer identification with members of the sports club’s social network and consumer identification with the sports club’s brand are positively related to consumer engagement. Furthermore, the value creation process is enhanced if the sport club approaches separately different dimensions of customer engagement in the social networks of the sports club.
Evaluating the Coupling Coordinated Development between Regional Ecological Protection and High-Quality Development: A Case Study of Guizhou, China
Authors: Cheng Zhe , Zhao Tianyu , Zhu Yixin , Li Hanshi
Published: October 2022

Promoting the coupling coordinated development between ecological protection and high-quality development is an important path to achieve sustainable regional development around the world. Taking Guizhou, China as a typical case, this study builds a comprehensive evaluation index system for ecological protection and high-quality development, and then uses the coupling coordination degree model to assess the spatiotemporal characteristics of ecological protection and high-quality development. According to the findings, Guizhou’s ecological protection index and high-quality development index both exhibit an upward trend and a center-edge spatial pattern, but they also exhibit a “spatial misalignment relationship”. The coupling coordination between ecological protection and high-quality development in Guizhou has shown a continuous growth trend from near-disorder to a primary coordination, with a spatial pattern of “central > western > eastern”. This study enriches the knowledge body of sustainable development, helps Guizhou make decisions that are best for ecological protection and high-quality development, and is useful as a reference for other regions and countries.
Exploring the Potential of Soil Salinity Assessment through Remote Sensing and GIS: Case Study in the Coastal Rural Areas of Bangladesh
Authors: Hossen Billal , Yabar Helmut , Faruque Md Jamal
Published: October 2022

Soil salinity is a negative impact of climate change, and it is a significant problem for the coastal region of Bangladesh, which has been increasing in the last four decades. The issue of soil salinity substantially limits the agricultural crop production in coastal areas. Therefore, a soil salinity assessment is essential for proper land-use planning in agricultural crop production. This research was carried out to determine the soil salinity area with different salinity levels in Barguna Sadar Upazila (sub-district). The remote sensing technique, which is a potentially quick yet effective method for the soil salinity estimation in data-scarce conditions, was applied. The methodology employed the Landsat 8 OLI dataset along with nine soil salinity indices to develop a soil salinity map. The maps were from Soil Resource Development Institute (SRDI), and low NDVI value (−0.01 to 0.48) was produced using satellite images illustrate the extent of the soil salinity for the study area. However, nine linear regressions, which were made between the pixel value of the satellite-based generated map and ground truth soil salinity data, that is, the EC value, indicate a maximum R2 value for the salinity index SI 7 = G × R/B, representing a value of 0.022. This minimal R2 value indicates a negligible relationship between the ground EC value and the pixel value of the salinity index generated map, inferring that the indices are not sufficient to assess the soil salinity. Nonetheless, this research’s findings offer a guide for researchers to investigate alternative geospatial approaches for this geophysical condition.
Human Pulmonary Dirofilariasis Due to Dirofilaria immitis: The First Italian Case Confirmed by Polymerase Chain Reaction Analysis, with a Systematic Literature Review
Authors: Palicelli Andrea , Veggiani Claudia , Rivasi Francesco , Gustinelli Andrea , Boldorini Renzo
Published: October 2022

Dirofilariasis is a zoonosis caused by nematodes of the genus Dirofilaria.Dirofilaria immitis is cosmopolitan as regards its distribution in animals, being responsible for human pulmonary dirofilariasis in the New World. However, human infections by Dirofilaria immitis are exceptional in Europe, and the previously reported Italian cases of pulmonary dirofilariasis were due to Dirofilaria repens. We performed a systematic literature review of the Italian cases of human dirofilariasis due to Dirofilariaimmitis according to the PRISMA guidelines. We also report the first autochthonous case of human pulmonary dirofilariasis due to Dirofilariaimmitis, confirmed by polymerase chain reaction analysis. The patient was a 60-year-old man who lived in the Po river valley and had never traveled abroad; on histological examination, the 2-cm nodule found in his right upper lung was an infarct due to a parasitic thrombotic lesion. Only one other autochthonous (but conjunctival) case due to Dirofilariaimmitis (molecularly confirmed) was previously found in the same geographic area. Climatic changes, the increasing movements of animal reservoirs and vectors, and new competent carriers have expanded the geographic distribution of the Dirofilaria species, increasing the risk of human infections. Our report demonstrates that at least some pulmonary Italian cases of human dirofilariasis are due to Dirofilaria immitis, as in the New World.
Why Has Digital Contact Tracing Worked Differently in Different Countries? Comment on Cao et al. The Impact of Digital Contact Tracing Apps Overuse on Prevention of COVID-19: A Normative Activation Model Perspective. Life 2022, 12, 1371
Authors: Giansanti Daniele
Published: October 2022

I am writing you regarding your interesting article “The Impact of Digital Contact Tracing Apps Overuse on Prevention of COVID-19: A Normative Activation Model Perspective” [...]
Thermal Energy Storage (TES) Prototype Based on Geopolymer Concrete for High-Temperature Applications
Authors: Rahjoo Mohammad , Goracci Guido , Gaitero Juan J. , Martauz Pavel , Rojas Esther , Dolado Jorge S.
Published: October 2022

Thermal energy storage (TES) systems are dependent on materials capable of operating at elevated temperatures for their performance and for prevailing as an integral part of industries. High-temperature TES assists in increasing the dispatchability of present power plants as well as increasing the efficiency in heat industry applications. Ordinary Portland cement (OPC)-based concretes are widely used as a sensible TES material in different applications. However, their performance is limited to operation temperatures below 400 °C due to the thermal degradation processes in its structure. In the present work, the performance and heat storage capacity of geopolymer-based concrete (GEO) have been studied experimentally and a comparison was carried out with OPC-based materials. Two thermal scenarios were examined, and results indicate that GEO withstand high running temperatures, higher than 500 °C, revealing higher thermal storage capacity than OPC-based materials. The high thermal energy storage, along with the high thermal diffusion coefficient at high temperatures, makes GEO a potential material that has good competitive properties compared with OPC-based TES. Experiments show the ability of geopolymer-based concrete for thermal energy storage applications, especially in industries that require feasible material for operation at high temperatures.
Role of Particle Shape on Ground Responses to a Circular Tunnel Excavation in Sandy Soil: Consequences from DEM Simulations
Authors: Zhang Zixin , Gao Xiaogeng , Wang Shuaifeng
Published: October 2022

Due to the sensitivity of sandy soil’s mechanical behavior to the particle shape, it is thus of importance for interpreting the effect of particle shape on the ground response induced by tunnel excavation in sandy formations. We conducted a series of 2D DEM (discrete element method) simulations on a common circular tunnel excavation in sandy soil with variable-shaped particles, which are characterized as two descriptors, i.e., aspect ratio (AR) and convexity (C). The macroscopic responses and the microscopic characteristics of the sandy ground are elaborated in detail. The simulation results show obvious asymmetrical features of the excavated ground, which results from the ground heterogeneity caused by the irregular particle shape. In addition, we investigate the roles of AR and C on the ground response and find that reducing AR or increasing C will enlarge the ground settlement, i.e., the sandy ground deformation is more sensitive to the particles with more irregular shapes. However, elongated particles are beneficial for the generation of soil arching with stronger bearing capacity and thus reduce the soil pressure on the tunnel lining. Our findings have important implications for the safety assessment of the tunnel excavation, as well as other underground structure construction in sandy formations.
Special Issue “Lightweight Structural Materials for Automotive and Aerospace”
Authors: Czerwinski Frank
Published: October 2022

Modern transport represents a vital part of the global economy, but it is also a significant source of pollutants, contributing 13% of overall greenhouse gas and 25% of CO2 emissions coming from the combustion of fossil fuels [...]
Failure Analysis of Ultra-High Molecular Weight Polyethylene Tibial Insert in Total Knee Arthroplasty
Authors: Manescu (Paltanea) Veronica , Antoniac Iulian , Antoniac Aurora , Paltanea Gheorghe , Miculescu Marian , Bita Ana-Iulia , Laptoiu Stefan , Niculescu Marius , Stere Alexandru , Paun Costel , Cristea Mihai
Published: October 2022

Knee osteoarthritis is treated based on total knee arthroplasty (TKA) interventions. The most frequent failure cause identified in surgical practice is due to wear and oxidation processes of the prothesis’ tibial insert. This component is usually manufactured from ultra-high molecular weight polyethylene (UHMWPE). To estimate the clinical complications related to a specific prosthesis design, we investigated four UHMWPE tibial inserts retrieved from patients from Clinical Hospital Colentina, Bucharest, Romania. For the initial analysis of the polyethylene degradation modes, macrophotography was chosen. A light stereomicroscope was used to estimate the structural performance and the implant surface degradation. Scanning electron microscopy confirmed the optical results and fulfilled the computation of the Hood index. The oxidation process in UHMWPE was analyzed based on Fourier-transform infrared spectroscopy (FTIR). The crystallinity degree and the oxidation index were computed in good agreement with the existing standards. Mechanical characterization was conducted based on the small punch test. The elastic modulus, initial peak load, ultimate load, and ultimate displacement were estimated. Based on the aforementioned experimental tests, a variation between 9 and 32 was found in the case of the Hood score. The oxidation index has a value of 1.33 for the reference sample and a maximum of 9.78 for a retrieved sample.
Effect of Tin Grain Orientation on Electromigration-Induced Dissolution of Ni Metallization in SnAg Solder Joints
Authors: Hsu Po-Ning , Lee Dai-Lung , Tran Dinh-Phuc , Shie Kai-Cheng , Tsou Nien-Ti , Chen Chih
Published: October 2022

In this study, symmetrical solder joints (Cu/Ni/SnAg2.3/Ni/Cu) were fabricated. They were electromigration (EM)-stressed at high (8 × 104 A/cm2) or low (1.6 × 104 A/cm2) current densities. Failures in the solder joints with different grain orientations under EM stressing were then characterized. Results show that Ni under-bump-metallurgy (UBM) was quickly dissolved into the solder joints possessing low angles between Sn c-axis and electron direction and massive NiCuSn intermetallic compounds formed in the Sn matrix. The diffusion rate of Ni increased with decreasing orientation grain angle. A theoretical model was also established to analyze the consumption rate of Ni UBM. Good agreement between the modeling and experimental results was obtained. Additionally, we found that voids were more likely to form in the solder joints under high EM stressing.
Effect of Aging Treatment on Microstructural Evolution and Mechanical Properties of the Electron Beam Cold Hearth Melting Ti-6Al-4V Alloy
Authors: Yu Jiaxin , Yin Zhengpei , Huang Zhirong , Zhao Shuai , Huang Haiguang , Yu Kun , Zhou Rongfeng , Xiao Han
Published: October 2022

Ti-6Al-4V (Ti64 or TC4) alloy is widely used in the industrial field. However, there have been few studies of the TC4 alloy melted by electron beam cold hearth melting (EBCHM) technology. Aging treatment has a considerable influence on the secondary α-phase in titanium alloys. Therefore, TC4 alloy melted by EBCHM technology was investigated in this study. The effect of different aging times on the microstructural evolution and mechanical properties of titanium alloy sheets was evaluated. The results showed that, with increase in aging time, the primary α-phase enlarged and grain globularization occurred. In addition, some transformed β-phases disappeared. The strength and Vickers hardness of the heat-treated sheets decreased, while the plasticity increased with increase in aging time, indicating that the mechanical properties developed with evolution of the microstructure. After aging at 560 °C for 2 h, the properties overall were optimal. The type of fracture of the samples was ductile fracture; the dimples became larger with increase in aging time. After heat treatment, the recrystallized nucleus, substructures and HAGBs increased, while the deformed structure and LAGBs decreased. Some grains had rotated following heat treatment, indicating that anisotropy was greatly reduced.
Seismic Performance of Precast Concrete Frame Beam-Column Connections with High-Strength Bars
Authors: Yu Jianbing , Zhang Ershuai , Xu Zhiqiang , Guo Zhengxing
Published: October 2022

As the construction industry is striding towards the industrialization of green buildings, a precast concrete frame beam-column joint with high-strength reinforcement was proposed. Simulate reversed cyclic loading was carried out on two precast connections and one cast-in-place connection to examine the seismic behavior of the proposed new precast connection. The main test variables between the two precast connections were the strength of the reinforcement at the bottom of the beam. The failure shape, hysteresis curve, skeleton curve, strength, deformation ability, stiffness degradation, and energy dissipation were monitored and compared with the cast-in-place connection. The findings of this paper showed that the precast joints had good strength reserve, and the seismic performance in the later stage of loading even exceeds the cast-in-place joints. It was also found that the plastic hinge zone of the beam could be moved away from the column surface via reinforcement method. Additionally, based on the experiment, a detailed nonlinear finite element analysis (FEA) method was developed to reproduce the test response of specific types of bending moment-resistant precast concrete beam-column connections under a reversed loading test, which provided a theoretical reference for further research of the connections.
Mutual Coupling Suppression of GPR Antennas by Depositing Wideband Meta-Absorber with Resistive Film
Authors: Zhou Yajun , Guo Minjie , Guo Linyan , Zhou Yi , Wei Changxin
Published: October 2022

The direct wave between the transceiver antenna negatively affects the dynamic range and imaging quality of ground penetrating radar (GPR). Suppressing this direct wave is a vital problem in enhancing the performance of the whole GPR system. In this paper, a Minkowski-fractal metamaterial absorber (MMA) with the resistive film is proposed in the GPR transceiver antenna to reduce the mutual coupling. The simulated and measured results indicate that this MMA has an effective wideband absorption in 1.0-8.0 GHz. And the thickness of MMA is only 0.007 λ0 (with respect to 2.0 GHz). This wideband MMA can reduce the mutual coupling of the proposed GPR transceiver antenna by an average of 10 dB. And it also mitigates the time-domain ringing problem of the transmit antenna. Real-world experiments demonstrate that the direct wave from the transmitting antenna can be reduced and the target echo arriving at the receiving antenna can be increased if this MMA is placed in the proposed transceiver antenna. This resistive film-based MMA offers great promise in realizing low-cost, compact, and lightweight GPR antennas, which can also be extended to high-frequency microwave imaging.
Prediction of Aero-Engine Remaining Useful Life Combined with Fault Information
Authors: Wang Chao , Peng Zhangming , Liu Rong
Published: October 2022

Since the fault information of an aero-engine is very important for the remaining useful life of an aero-engine, the paper proposes to combine the fault information for the remaining useful life prediction of an aero-engine. Firstly, we preprocessed the signals of the dataset. Next, the preprocessed signals were used to train a CNN (convolutional neural network)-based fault diagnosis model and obtain fault features from the model. Then, we combined BIGRU (bidirectional gated recurrent unit) and the fault features to predict the remaining useful life of the aero-engine. We used the CMAPSS (commercial modular aviation propulsion system simulation) dataset to verify the effectiveness of the proposed method. After that, comparison experiments with different parameters, structures, and models were conducted in the paper.
Taikobot: A Full-Size and Free-Flying Humanoid Robot for Intravehicular Astronaut Assistance and Spacecraft Housekeeping
Authors: Zhang Qi , Zhao Cheng , Fan Li , Zhang Yulin
Published: October 2022

This paper proposes a full-size and free-flying humanoid robot named Taikobot that aims to assist astronauts in a space station and maintain spacecrafts between human visits. Taikobot adopts a compact and lightweight (∼25 kg) design to work in microgravity, which also reduces launch costs and improves safety during human–robot collaboration. Taikobot’s anthropomorphic dual arm system and zero-g legs allow it to share a set of intravehicular human–machine interfaces. Unlike ground-walking robots, Taikobot maneuvers in a novel push–flight–park (PFP) strategy as an equivalent astronaut in a space station to maximize workspace and flexibility. We propose a PFP motion planning and control method based on centroidal dynamics and multi-contact model. Based on the proposed method, we carried out extensive simulations and verified the feasibility and advantages of the novel locomotion strategy. We also developed a prototype of Taikobot and carried out several ground experiments on typical scenarios where the robot collaborates with human astronauts. The experiments show that Taikobot can do some simple and repetitive tasks along with astronauts and has the potential to help astronauts improve their onboard working efficiency.
Conditional Synthesis of Blood Glucose Profiles for T1D Patients Using Deep Generative Models
Authors: Mujahid Omer , Contreras Ivan , Beneyto Aleix , Conget Ignacio , Giménez Marga , Vehi Josep
Published: October 2022

Mathematical modeling of the glucose–insulin system forms the core of simulators in the field of glucose metabolism. The complexity of human biological systems makes it a challenging task for the physiological models to encompass the entirety of such systems. Even though modern diabetes simulators perform a respectable task of simulating the glucose–insulin action, they are unable to estimate various phenomena affecting the glycemic profile of an individual such as glycemic disturbances and patient behavior. This research work presents a potential solution to this problem by proposing a method for the generation of blood glucose values conditioned on plasma insulin approximation of type 1 diabetes patients using a pixel-to-pixel generative adversarial network. Two type-1 diabetes cohorts comprising 29 and 6 patients, respectively, are used to train the generative model. This study shows that the generated blood glucose values are statistically similar to the real blood glucose values, mimicking the time-in-range results for each of the standard blood glucose ranges in type 1 diabetes management and obtaining similar means and variability outcomes. Furthermore, the causal relationship between the plasma insulin values and the generated blood glucose conforms to the same relationship observed in real patients. These results herald the aptness of deep generative models for the generation of virtual patients with diabetes.
Complex Color Space Segmentation to Classify Objects in Urban Environments
Authors: Cardenas-Cornejo Juan-Jose , Ibarra-Manzano Mario-Alberto , Razo-Medina Daniel-Alberto , Almanza-Ojeda Dora-Luz
Published: October 2022

Color image segmentation divides the image into areas that represent different objects and focus points. One of the biggest problems in color image segmentation is the lack of homogeneity in the color of real urban images, which generates areas of over-segmentation when traditional color segmentation techniques are used. This article describes an approach to detecting and classifying objects in urban environments based on a new chromatic segmentation to locate focus points. Based on components a and b on the CIELab space, we define a chromatic map on the complex space to determine the highest threshold values by comparing neighboring blocks and thus divide various areas of the image automatically. Even though thresholds can result in broad segmentation areas, they suffice to locate centroids of patches on the color image that are then classified using a convolutional neural network (CNN). Thus, this broadly segmented image helps to crop only outlying areas instead of classifying the entire image. The CNN is trained to use six classes based on the patches drawn from the database of reference images from urban environments. Experimental results show a high score for classification accuracy that confirms the contribution of this segmentation approach.
Exploring Online Activities to Predict the Final Grade of Student
Authors: Gaftandzhieva Silvia , Talukder Ashis , Gohain Nisha , Hussain Sadiq , Theodorou Paraskevi , Salal Yass Khudheir , Doneva Rositsa
Published: October 2022

Student success rate is a significant indicator of the quality of the educational services offered at higher education institutions (HEIs). It allows students to make their plans to achieve the set goals and helps teachers to identify the at-risk students and make timely interventions. University decision-makers need reliable data on student success rates to formulate specific and coherent decisions to improve students’ academic performance. In recent years, EDM has become an effective tool for exploring data from student activities to predict their final grades. This study presents a case study for predicting the students’ final grades based on their activities in Moodle Learning Management System (LMS) and attendance in online lectures conducted via Zoom by applying statistical and machine learning techniques. The data set consists of the final grades for 105 students who study Object-Oriented Programming at the University of Plovdiv during the 2021–2022 year, data for their activities in the online course (7057 records), and attendance to lectures (738). The predictions are based on 46 attributes. The Chi-square test is utilized to assess the association between students’ final grades and event context (lectures, source code, exercise, and assignment) and the relationships between attendance at lectures and final results. The logistic regression model is utilized to assess the actual impact of event context on “Fail” students in a multivariate setup. Four machine learning algorithms (Random Forest, XGBoost, KNN, and SVM) are applied using 70% of training data and 30% of test data to predict the students’ final grades. Five-fold cross validation was also utilized. The results show correlations between the students’ final grades and their activity in the online course and between students’ final grades and attendance at lectures. All applied machine learning algorithms performed moderately well predicting the students’ final results, as the Random Forest algorithm obtained the highest prediction accuracy—78%. The findings of the study clearly show that the Random Forest algorithm may be used to predict which students will fail after eight weeks. Such data-driven predictions are significant for teachers and decision-makers and allow them to take measures to reduce the number of failed students and identify which types of learning resources or student activities are better predictors of the student’s academic performance.
Natural Transformations between Induction and Restriction on Iterated Wreath Product of Symmetric Group of Order 2
Authors: Im Mee Seong , Oğuz Can Ozan
Published: October 2022

Let CAn=C[S2≀S2≀⋯≀S2] be the group algebra of an n-step iterated wreath product. We prove some structural properties of An such as their centers, centralizers, and right and double cosets. We apply these results to explicitly write down the Mackey theorem for groups An and give a partial description of the natural transformations between induction and restriction functors on the representations of the iterated wreath product tower by computing certain hom spaces of the category of ⨁m≥0(Am,An)−bimodules. A complete description of the category is an open problem.
Implications of CSR Practices for a Development Supply Chain in Alleviating Farmers’ Poverty
Authors: Zhang Qingyu , Luo Tianlong
Published: October 2022

To alleviate farmer poverty, this paper investigates the effect of a retailer’s different socially responsible practices on a two-echelon supply chain consisting of one rural (poor) farmer, one suburban farmer, and one common retailer. Different from a commercial supply chain (whose members’ objectives are to maximize their profits) and a humanitarian supply chain (whose objective is to save more people, rather than to prioritize profits), the paper aims to study a development supply chain where the CSR-conscious retailer aims to lift the poor farmer out of poverty through cost sharing, altruistic practices, or fairness practices. Can the CSR-conscious retailer (and the development supply chain) do well by doing good? To answer the above question, four models of potential CSR investment are established and analyzed. Considering the different influences of the retailer’s CSR practices, this paper uses a Stackelberg game to analyze the decisions and profits of the farmers and the retailer in these four models. Our study finds that, first, the retailer’s CSR practices can improve the whole supply chain’s performance, which means that the supply chain has the potential to achieve the Pareto improvement for both the farmers and the retailer. Second, the retailer’s CSR practices yield benefits while implementing cost-sharing or fairness practices. Third, the rural farmer always benefits from the retailer’s CSR practices and may prefer the altruistic practice from which they can benefit the most. In addition, to benefit their profit more, the rural farmer should grow high- or low-value-added crops rather than medium-value-added ones. Fourth, from the suburban farmer’s perspective, the retailer’s CSR practices are not beneficial for their performance. However, the extent to which the suburban farmer’s performance decreases is much lower than the extent to which the rural farmer’s performance improves. The results of this paper might be used by stakeholders to alleviate poverty.
The Fast Generation of the Reachable Domain for Collision-Free Asteroid Landing
Authors: Zhao Yingjie , Yang Hongwei , Hu Jincheng
Published: October 2022

For the mission requirement of collision-free asteroid landing with a given time of flight (TOF), a fast generation method of landing reachable domain based on section and expansion is proposed. First, to overcome the difficulties of trajectory optimization caused by anti-collision path constraints, a two-stage collision-free trajectory optimization model is used to improve the efficiency of trajectory optimization. Second, the velocity increment under a long TOF is analyzed to obtain the distribution law of the reachable domain affected by the TOF, and the generation problem of the reachable domain is transformed into the solution problem of the initial boundary and the continuous boundary. For the initial boundary, the section method is used to acquire a point on the boundary as the preliminary reachable domain boundary. The solution of continuous boundary is based on the initial boundary continuously expanding the section into the reachable domain until the boundary is continuous. Finally, the proposed method is applied to the asteroids 101955 Bennu and 2063 Bacchus. The simulation results show that this method can quickly and accurately obtain the reachable domain of collision-free asteroid landing in a given TOF and is applicable to different initial positions.
A Revised Continuous Observation Length Model of Rough Contact without Adhesion
Authors: Zhang Lan , Wen Jing , Liu Ming , Xing Guangzhen
Published: October 2022

The real contact area of rough surfaces has significant importance in many engineering applications, such as tribology, wear, lubrication and seals. A continuous observation length-dependent mechanic model of rough contact without adhesion is proposed, which assumes that the rough surface is divided into ideal subplanes. However, the model ignores the elastoplastic deformation of asperities, and the standard deviation of ideal subplanes’ heights is assumed to vary linearly with continuous observation length, which is not precise for all the surface fractal dimensions. In this work, a revised continuous observation length model is proposed with elastic, elastoplastic and fully plastic stages. The expressions of force and real contact areas are derived. For surfaces with different fractal dimensions, the quadratic polynomial, cubic polynomial and power relationships between standard deviation and observation length are proposed, respectively. In addition, the influences of the dimensionless observation length, fractal dimension and equivalent elastic modulus on the real contact areas in different contact stages are also analyzed. It can be concluded that the quadrate real contact area decreases as the dimensionless observation length decreases, which can be applied to the percolation theory for leak seal problems.
Machine Learning-Based Estimation of the Compressive Strength of Self-Compacting Concrete: A Multi-Dataset Study
Authors: Hoang Nhat-Duc
Published: October 2022

This paper aims at performing a comparative study to investigate the predictive capability of machine learning (ML) models used for estimating the compressive strength of self-compacting concrete (SCC). Seven prominent ML models, including deep neural network regression (DNNR), extreme gradient boosting machine (XGBoost), gradient boosting machine (GBM), adaptive boosting machine (AdaBoost), support vector regression (SVR), Levenberg–Marquardt artificial neural network (LM-ANN), and genetic programming (GP), are employed. Four experimental datasets, compiled in previous studies, are used to construct the ML-based methods. The models’ generalization capabilities are reliably evaluated by 20 independent runs. Experimental results point out the superiority of the DNNR, which has excelled other models in three out of four datasets. The XGBoost is the second-best model, which has gained the first rank in one dataset. The outcomes point out the great potential of the utilized ML approaches in modeling the compressive strength of SCC. In more details, the coefficient of determination (R2) surpasses 0.8 and the mean absolute percentage error (MAPE) is always below 15% for all datasets. The best results of R2 and MAPE are 0.93 and 7.2%, respectively.
Correct and Stable Algorithm for Numerical Solving Nonlocal Heat Conduction Problems with Not Strongly Regular Boundary Conditions
Authors: Sadybekov Makhmud A. , Pankratova Irina N.
Published: October 2022

For a nonlocal initial-boundary value problem for a one-dimensional heat equation with not strongly regular boundary conditions of general type, an approximate difference scheme with weights is constructed. A correct and stable algorithm for the numerical solving of the difference problem is proposed. It is proven that the difference scheme with weights is stable and its solution converges to the exact solution of the differential problem in the grid L2h-norm. Stability conditions are established. An estimate of the numerical solution with respect to the initial data and the right-hand side of the difference problem is given.
Improvement of Gait after Robotic-Assisted Training in Children with Cerebral Palsy: Are We Heading in the Right Direction?
Authors: De Luca Rosaria , Bonanno Mirjam , Settimo Carmela , Muratore Rosalia , Calabrò Rocco Salvatore
Published: October 2022

Cerebral palsy (CP) is a non-progressive congenital neurological disorder that affects different physical and cognitive functions in children. In addition to standard rehabilitation, advanced robotic gait devices are novel tools that are becoming progressively more common as part of the treatment of CP. The aim of this study is to evaluate the effects of Lokomat training, in addition to conventional rehabilitation, on the motor function and quality of life of children with ataxic-spastic CP (ASCP). Ten children with ASCP who attended the Robotic Rehabilitation OutClinic of the IRCCS Centro Neurolesi “Bonino Pulejo”, from April to June 2019, were enrolled in this study. They received twenty-four robotic rehabilitation sessions, twice a week for three months, each session lasting about 45 min. They were also provided with conventional physical and occupational therapy. After the innovative training, we found significant changes in the children’s outcomes, i.e., in GMFM (p < 0.001), with significant improvements in sitting (p < 0.03) and walking (p < 0.03). Moreover, the quality of life of the young patients, evaluated by their parents, significantly improved (p < 0.005). The use of robotic systems could be considered to be an effective complementary treatment to improve gait, as well as quality of life, in children with CP.
Parameter Study on the Recycling of LFP Cathode Material Using Hydrometallurgical Methods
Authors: Gerold Eva , Lerchbammer Reinhard , Antrekowitsch Helmut
Published: October 2022

The need to recover critical elements from lithium-ion batteries is undisputed. The further development of cathode materials and the move towards cheaper alternatives make it necessary to adapt the corresponding hydrometallurgical recycling processes. In the best case, however, a process is so flexibly structured and designed that it can be used for a variety of cathode materials with different compositions. The leaching of nickel manganese cobalt oxide with sulfuric acid and a reducing agent has already been demonstrated and optimized in previous research work. Based on these data, an evaluation of the process as well as a parameter study for lithium iron phosphate cathode material, which has recently been used with increasing frequency but has a significantly lower valuable metal content, was carried out within the scope of this publication. By using the synergy effects that occur, an optimized parameter combination for the leaching of the critical element lithium could be found and further critical factors identified.
Microbial Community, Co-Occurrence Network Relationship and Fermentation Lignocellulose Characteristics of Broussonetia papyrifera Ensiled with Wheat Bran
Authors: Wang Wenbo , Nie Yanshun , Tian Hua , Quan Xiaoyan , Li Jialin , Shan Qiuli , Li Hongmei , Cai Yichao , Ning Shangjun , Santos Bermudez Ramon , He Wenxing
Published: October 2022

Broussonetia papyrifera has a high lignocellulose content leading to poor palatability and low digestion rate of ruminants. Thus, dynamic profiles of fermentation lignocellulose characteristics, microbial community structure, potential function, and interspecific relationships of B. papyrifera mixing with wheat bran in different ratios: 100:0 (BP100), 90:10 (BP90), 80:20 (BP80), and 65:35 (BP65) were investigated on ensiling days 5, 15, 30, and 50. The results showed that adding bran increased the degradation rate of hemicellulose, neutral detergent fiber, and the activities of filter paper cellulase, endoglucanase, acid protease, and neutral protease, especially in the ratio of 65:35. Lactobacillus, Pediococcus, and Weissella genus bacteria were the dominant genera in silage fermentation, and Pediococcus and Weissella genus bacteria regulated the process of silage fermentation. Compared with monospecific B. papyrifera silage, adding bran significantly increased the abundance of Weissella sp., and improved bacterial fermentation potential in BP65 (p < 0.05). Distance-based redundancy analysis showed that lactic acid bacteria (LAB) were significantly positive correlated with most lignocellulose content and degrading enzymes activities, while Monascus sp. and Syncephalastrum sp. were opposite (p < 0.05). Co-occurrence network analysis indicated that there were significant differences in microbial networks among different mixing ratios of B. papyrifera silage prepared with bran. There was a more complex, highly diverse and less competitive co-occurrence network in BP65, which was helpful to silage fermentation. In conclusion, B. papyrifera ensiled with bran improved the microbial community structure and the interspecific relationship and reduced the content of lignocellulose.
The Spike Protein of SARS-coV2 19B (S) Clade Mirrors Critical Features of Viral Adaptation and Coevolution
Authors: Hussein Bidour K. , Ibrahium Omnia M. , Alamin Marwa F. , Ahmed Lamees A. M. , Abuswar Safa A. E. , Abdelraheem Mohammed H. , Ibrahim Muntaser E.
Published: October 2022

Pathogens including viruses evolve in tandem with diversity in their animal and human hosts. For SARS-coV2, the focus is generally for understanding such coevolution on the virus spike protein, since it demonstrates high mutation rates compared to other genome regions, particularly in the receptor-binding domain (RBD). Viral sequences of the SARS-coV2 19B (S) clade and variants of concern from different continents were investigated, with a focus on the A.29 lineage, which presented with different mutational patterns within the 19B (S) lineages in order to learn more about how SARS-coV2 may have evolved and adapted to widely diverse populations globally. Results indicated that SARS-coV2 went through evolutionary constrains and intense selective pressure, particularly in Africa. This was manifested in a departure from neutrality with excess nonsynonymous mutations and a negative Tajima D consistent with rapid expansion and directional selection as well as deletion and deletion–frameshifts in the N-terminal domain (NTD region) of the spike protein. In conclusion, we hypothesize that viral transmission during epidemics through populations of diverse genomic structures and marked complexity may be a significant factor for the virus to acquire distinct patterns of mutations within these populations in order to ensure its survival and fitness, explaining the emergence of novel variants and strains.
Use of Antigen Combinations to Address Complex Leishmania-Seropositivity Patterns in Dogs Living in Canine Leishmaniosis Endemic Regions of Portugal
Authors: Lima Carla Silva , Esteves Sofia , Costa Inês , Brancal Hugo , Lima Clara , Amorim Célia , Cardoso Luís , Santarém Nuno , Cordeiro-da-Silva Anabela
Published: October 2022

Canine leishmaniosis (CanL) is a vector-borne disease caused by Leishmania infantum. Infection in dogs can result in a disease with non-specific clinical signs or in a subclinical condition. Infection diagnosis is crucial to guide public health measures considering the zoonotic potential of L. infantum. Serological approaches to detect infection with a reduced antigen panel potentially limit the quality of the information obtained. To evaluate the impact of using distinct antigens in a serological survey, a cohort with 390 dogs from endemic regions in Portugal was subjected to a serological evaluation using ELISA and DAT. Using ELISA, six Leishmania-specific antigens in conjunction with a non-related antigen, Escherichia coli soluble antigens, were evaluated. The global seroprevalence was 10.5% for DAT and 15.4 to 23.1% for ELISA, depending on the antigen for the latter. Still, only 8.2% of the animals were seropositive to all Leishmania-specific antigens. Importantly, a further 31.0% presented antigen-dependent seropositivity. Considering this observation, a serological score system was proposed and validated to address the complex serology results. With this system, the overall dog seropositivity was 26.9%. This work highlights the limitations of single-antigen serological surveys and presents an approach that might contribute to the establishment of CanL-specific serological profiles.
Genomic and Phylogenetic Characterization of Rhodopseudomonas infernalis sp. nov., Isolated from the Hell Creek Watershed (Nebraska)
Authors: Humphrey Christine E. , Burnett Nicole , Dubey Shivangi , Kyndt John A.
Published: October 2022

The genus Rhodopseudomonas is known for its versatile metabolic capabilities and has been proposed to be used in a wide variety of innovative applications, ranging from biohydrogen and electricity production, bioremediation and as biostimulant in agriculture. Here, we report the isolation, characterization and genome sequence analysis of a novel Rhodopseudomonas species, strain HC1, isolated from the Hell Creek urban native restoration area. Whole genome-based analysis, average nucleotide identity (ANI) comparison, and growth characteristics identified this isolate as a new species of the Rhodopseudomonas genus, for which we propose the name Rhodopseudomonas infernalis sp. nov. Besides containing several nitrogenases for nitrogen fixation and hydrogen production, the HC1 genome encodes a unique gene cluster, not found in any other Rhodopseudomonas species, which encodes genes for the degradation of yet-unidentified aromatic PCB-type chemicals with potentially interesting biotechnological applications. The genomic features of Rps. infernalis HC1 indicate that it plays a positive role in the degradation of anthropogenic substances and aids the restoration of the Hell Creek watershed by contributing to N2 and carbon fixation and plant growth; however, the genome also contains several antibiotic resistance genes, indicating a broad range of antibiotic resistance in this environmental isolate.