Battery packs of electric vehicles are typically composed of lithium-ion batteries with aluminum and copper acting as cell terminals. These terminals are joined together in series by means of connector tabs to produce sufficient power and energy output. Such critical electrical and structural cell terminal connections involve several challenges when joining thin, highly reflective and dissimilar materials with widely differing thermo-mechanical properties. This may involve potential deformation during the joining process and the formation of brittle intermetallic compounds that reduce conductivity and deteriorate mechanical properties. Among various joining techniques, laser welding has demonstrated significant advantages, including the capability to produce joints with low electrical contact resistance and high mechanical strength, along with high precision required for delicate materials like aluminum and copper. The primary objective of this study was to join 0.8 mm thick aluminum and copper tabs through the laser welding methodology, with a particular emphasis on optimizing welding parameters including laser output power and welding speed to achieve robust and reliable connections. Through systematic experimentation, the influence of these parameters on weld strength and joint properties was explored. Utilizing a normalized laser power of 0.87 and a normalized welding speed of 0.75, a normalized lap weld strength of 39.62 was achieved for 25.4 mm wide thin sheets. Furthermore, formation and characterization of intermetallic compounds (IMC) along with microhardness distribution within the weld zone were examined. This investigation provides valuable insights into mechanical properties of the cell connections and their potential influence on overall joint durability.

Abstract Introduction: Nodal Metastasis as an Immune Indicator in Cancer (Ca) Therapy Staging (sg) is widely used to identify appropriate treatment options & implement therapy. Tumor-Node-Metastasis (TNM) is the most utilized sg system. In it, nodal involvement is viewed simply as an adverse metric without biologic connotation, and gross metastasis (M1) eclipses other variables and denotes the least favorable sg. Ca’s ability to thrive within the lymph node itself was intriguing to us in the immune-oncology (IO) era. Failure to overcome an immunogenic ca (e.g., dysfunctional apoptosis) leads to T-cell exhaustion (TCE) typified by PD-1 expression. Immune Checkpoint Inhibitors (ICI) address TCE by intercepting the PD-1:PDL-1 synapse. We reasoned that immune actions are distinct in tumor beds vs nodes & hypothesized that immunogenic N(+), implies ca’s ability to defend itself (e.g., PDL-1 expression); N(0), reflects immune susceptibility and effective clearance outside the tumor bed. In the latter scenario, TCE is nonexistent; ICIs are less beneficial. Tumor beds (T, M) are sanctuaries exempt from immune action due to factors such as hypoxia, acidity, and poor tumor vasculature which lead to poor T-cell trafficking, to name a few. M1 develop from circulating ca stem cells, an immune-exempt entity. Methods: We examined the interaction between ICIs & nodal involvement dichotomizing surveillance, epidemiology and end results SEER cases into N(0) or N(+) within M1 melanoma & lung cancer. 2005, 2015-17 denote pre-, and post ICI, respectively to provide mature survival data. Results: Table 1 depicts the 4- or 5-year overall survival in the specified subsets. Conclusions: ICI benefit is more prominent in N(+) ca, where TCE is likely. N(0) ca represents immune-prone ca with less TCE & need to be viewed as a biologically distinct subset. Agents influencing T-cell access (angiogenic)/functionality should be considered in these cases. Finally, we suggest that PDL-1 testing should specify testing sites as nodal vs tumor bed expression. Expectations SEER results: % Overall Survival at 5-y (melanoma) or 4-y (Lung ca) Pre-ICI Post ICI Metric Melanoma Mechanism 2005 2015 Increment in 5yr OS N(0) favorable prognosis Immunogenic tumor N(0): 302 cases 20 29 8 (20 -12) N+ Predicts benefit to ICI T-cell exhaustion in N(+) only N(+): 210 cases 12 37 N(+): +25 > N(0): +9 2005 2017 Increment in 4yr OS Lung Cancer N(0) similar to N(+) Less immunogenic tumor N(0) 9,583 cases 18 18 4 (18 -14) N+ Predicts benefit to ICI T-cell exhaustion in N(+) only N(+): 17,887 cases 14 20 +6 Citation Format: Bradley Fugere, Jim Chen, Tyler C. Fugere, Farah Mazahreh, Nishanth Thalambadu, A Mazin Safar. Nodal metastasis as an immune indicator in cancer (ca) therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3856.

ABSTRACT In this paper we consider a project leader assignment problem involving many projects that need to be executed during fixed intervals of time. Further, each project requires a manager or project leader with a specified minimum level of expertise. This implies that a project leader with a higher level of expertise may be assigned to a project that requires a lower level of expertise, but not vice versa. Obviously, the objective is to determine an optimal staffing strategy that would help us complete all the projects on time. This problem is very similar to some of the well-known resource allocation or scheduling problems in which a resource with a higher capacity or size is assigned to a task that requires a resource with a smaller capacity or size, but not vice versa. In the literature, problems with this type of structure are often called Hierarchical Class Scheduling Problems (HCSP). We exploit the similarity between our staffing problem and the HCSP, and transform it into a multi-commodity network flow problem and impose an additional constraint that the values of the variables be either zero or one. This additional constraint forces us to treat the original multi-commodity network flow problem or the corresponding linear programming problem as an integer programming problem. It is well-established, on the basis of its combinatorial structure and computational complexity, that the integer programming problem belongs to the class of NP-hard problems and there are no efficient (polynomial-time) algorithms to solve it. Here we describe optimization techniques that are derived from a combination of integer programming and heuristic methods to obtain near-optimal solutions to our staffing problem and the related HCSP. Keywords Hierarchical Class Scheduling, NP-hard Problems, Integer Programming, Heuristic Methods

Strict environmental regulations are driving the automotive industry toward electric vehicles as they offer zero emissions. A key component in electric vehicles is the electric motor, where the stator and rotor are manufactured from stacks of thin electrical steel sheets. The electrical steel sheets can be cut in different ways, and the cutting methods may significantly affect the fatigue strength of the component. It is important to understand the effect of the cutting processes on the fatigue properties of electrical steel to ensure there is no premature failure of the electric motor resulting from an improper cutting process. This investigation compared the effect of three different edge preparation methods (stamping, CNC machining, and waterjet cutting) on the fatigue performance of 0.27mm thick electrical steel sheets. To investigate the effect of the edge finish on fatigue behavior, surface roughness was measured for these different samples. It was determined that the CNC machined samples had the lowest overall roughness over the cut edge, followed by the stamped samples, and the waterjet samples with the worst finish. The fatigue life followed a similar trend where CNC machined samples had the longest life, and the waterjet samples had the lowest life under the same stress amplitude. While the CNC samples had the greatest overall life, the stamped samples could withstand the largest alternating stress out of the three cutting processes because of the residual stresses induced by the stamping process. Additionally, the stamped samples had very close life to the CNC machines samples in the high cycle regime. An investigation was carried out to determine the relationship between surface roughness and residual stress to the fatigue life of the electrical steel.

Electrical steels are silicon alloyed steels that possess great magnetic properties, making them the ideal material choice for the stator and rotor cores of electric motors. They are typically comprised of laminated stacks of thin electrical steel sheets. An electric motor can reach high temperatures under a heavy load, and it is important to understand the combined effect of temperature and load on the electrical steel’s performance to ensure the long life and safety of electric vehicles. This study investigated the fatigue strength and failure behavior of a 0.27mm thick electrical steel sheet, where the samples were prepared by a stamping process. Stress-control fatigue tests were performed at both room temperature and 150°C. The S-N curve indicated a decrease in the fatigue strength of the samples at the elevated temperature compared to the room temperature by 15-25 MPa in the LCF and HCF regimes, respectively. Looking at the fracture surface, the room temperature samples at both the low- and high-cycle regimes showed some intergranular cleavage facets along with predominant transgranular facets in the crack initiation zone and transitioned to only transgranular cleavage facets in the crack propagation zone. In contrast, the high-temperature samples showed a smaller fatigue damage zone, and outside of this zone, the main failure mechanism was severe necking for both the low- and high-cycle samples. An important finding here was that the crack always initiated from the breakaway zone on the stamped edge of the samples. The higher temperature adversely affected the fatigue strength, as the higher temperature releases residual stresses and annihilates dislocation density induced during the sheet manufacturing and sample preparation, resulting in shorter fatigue life.

Retrosynthesis and forward synthesis prediction are fundamental challenges in organic synthesis, computer-aided synthesis planning (CASP), and computer-aided drug design (CADD). The objective is to predict plausible reactants for a given target product and its corresponding inverse task. With the rapid development of deep learning, numerous approaches have been proposed to solve this problem from various perspectives. The methods based on molecular graphs benefit from their rich features embedded inside but face difficulties in applying existing sequence-based data augmentations due to the permutation invariance of graph structures. In this work, we propose SeqAGraph, a template-free approach that annotates input graphs with its root atom index to ensure compatibility with sequence-based data augmentation. The matrix product for global attention in graph encoders is implemented by indexing, elementwise product, and aggregation to fuse global attention with local message passing without graph padding. Experiments demonstrate that SeqAGraph fully benefits from molecular graphs and sequence-based data augmentation and achieves state-of-the-art accuracy in template-free approaches.

Determining changes in the protein's thermal stability following mutations is critical in protein engineering and understanding pathogenic missense mutations. Despite the development of various computational methods to predict the effects of single-point mutations, their accuracy remains limited. In this study, we propose a new computational method, OmeDDG, that more accurately predicts mutation-induced Gibbs free energy changes in protein folding (ΔΔG). OmeDDG takes the sequences of wild-type and mutant proteins as input, utilizes OmegaFold to obtain the 3D structure, employs a convolutional neural network to extract structural features, and combines them with protein mutation features and pretraining features to predict the stability of single-point mutations in proteins. We performed a comprehensive comparison between OmeDDG and other available prediction methods on four blind test datasets, confirming that OmeDDG can effectively enhance protein mutation prediction performance. Notably, on the antisymmetric dataset Ssym, OmeDDG achieves the best performance, demonstrating favorable antisymmetry with PCC = 0.79 and RMSE = 0.96 for forward mutations and PCC = 0.77 and RMSE = 0.97 for reverse mutant types.

Electrical steel, also known as silicon steel, is a ferromagnetic material that is often used in electric vehicles (EVs) for stator and rotor applications. Since the design and manufacturing of rotors require the use of laminated thin electrical steel sheets, the fatigue characterization of these single sheets is of interest. In this study, a 0.27mm thick non-oriented electrical steel sheet was tested under cyclic loading in the load-controlled mode with the load ratio R = 0.1 at room temperature. The specimens were prepared using the Computer Numerical Control (CNC) machining method. The Smith-Watson-Topper mean stress correction was used to find the equivalent fully reversed stress-life (S-N) curve. The Basquin equation was used to describe the fatigue strength of the electrical steel and the fatigue parameters were extracted. Furthermore, a design curve with a reliability of 90% and a confidence level of 90% was generated using Owen’s Tolerance Limit method. The fracture mechanisms under cyclic loading were also studied using a scanning electron microscope. Crack initiation was determined to initiate from one edge and propagate to the other. Although the fracture mechanism was transgranular, the fracture surface displayed distinct regions of fatigue damage and cleavage fracture. The presence of aluminium nitrate precipitate particles contributing to crack initiation was confirmed using the energy dispersive x-ray spectroscopy technique.

ABSTRACT In many operational scheduling problems, we encounter situations wherein a resource with a higher capacity can undertake a job that requires a resource with a lower capacity, but not vice versa. For example, a crane with a lifting capacity of 40 tons can be used, if necessary, to lift a load of 27 tons at a construction site, but a crane with a lifting capacity of only 30 tons cannot be used to lift a load of 35 tons. Another familiar example is the assignment of airplanes to different flights. In almost all such cases, a resource that has a higher capacity is a lot more expensive than the one with a lower capacity. Further, each task has to be completed in a time interval that may be fixed or flexible. In the literature, job scheduling problems like these are called Hierarchical Class Scheduling Problems (HCSP), because of the hierarchical structure of their capacity requirements. For problems like these, currently no viable algorithmic techniques are available to determine the optimal mix of resources or processors needed to complete all the jobs on schedule, in spite of the availability of modern powerful computers. Scheduling problems of this type, among many others, are categorized as NP-hard problems in the specialized field of computer science that deals with the subject of computational complexity and solvability of problems. In this paper, we consider a special case of the Hierarchical Class Scheduling Problem (HCSP) and present some propositions that help us find the optimal solution for the special case. Keywords Fixed Interval Scheduling, Hierarchical Class Scheduling, NP-hard Problems

ABSTRACT This paper points out that US-China relations have entered into a new phase of prolonged, fierce technological competition, particularly as dominance in advanced technology will lead to dominance of the world. At the center of the technological conflicts is 5G, which is critical for the development and rise of emerging, cutting-edge technologies. This paper discusses the US campaign to constrain Huawei and reviews the rapid adoption of China’s smart cities which, above all, are a platform for censorship and surveillance. It is found that the attitudes toward Huawei and the World Press Freedom Index (WPFI) are highly correlated. A k-means cluster analysis yields two divided blocs: one with a WPFI below 37.7 and led by US; and the other, with a WPFI above 39.7 and led by China. Although the US can significantly slow down China’s high-tech ambitions, China will eventually achieve self-reliance through its technological foundations and nationwide campaign to be technologically independent. A clear demarcation in technology usage could be a wall of worry for the world. Keywords Belt and Road Initiative; Entity List; Huawei; smart city; 5G

Pantograph catenary contact point is an important monitoring object during pantograph catenary operation, which reflects the state of pantograph catenary operation. However, due to the relatively small contact area of the target area, it is still a challenge to locate the contact point quickly and accurately. Therefore, we propose a two-stage detection method of rigid pantograph catenary contact points based on deep convolution neural network. Firstly, yolov3 network is used to locate the pantograph catenary contact part, which can obtain the target area including contact points. Then, four key points generated by the intersection of rigid pantograph and catenary can be obtained by using the key point detection network in the target area. Finally, the positioning of pantograph catenary contact points is obtained by geometric calculation. The experimental results on the railway operation data set collected by the traction Laboratory of Southwest Jiaotong University show the effectiveness of the method.

ABSTRACT The purposes of the paper are to understand how the state of the world order will change and how this change will impact the choice of business strategies (i.e., standardization versus customization) for companies. To anticipate the future world order, Huntington and Fukuyama’s contradicting theories are employed. By using UN’s Human Development Index, it is tested if the world will be one big global culture or will be divided into several civilizations. The findings provided support for Huntington’s clustered civilizations approach in which the world would be divided into multi-centered cultures based on religion and ethnicity. Based on the results, the paper recommends the companies to adapt customization as their grand business strategy. Keywords Huntington, Fukuyama, Grand Strategy, Regional orientation, Human Development Index, Customization, Standardization, Homogeneity/diversity, Clusters.

ABSTRACT The purpose of this study was to explore the perceptions and knowledge of college students regarding the COVID-19 outbreak. A cross-sectional design was used and data were collected over 4 weeks from March to April 2021 through an online survey. A total of 106 usable responses were collected from undergraduate students at two universities in the southern United States. Respondents reported that most of their information regarding COVID-19 comes from media (print/television/radio) and social media. Participants showed only acceptable levels of knowledge about vaccinations. Data suggest 75 percent of respondents are likely or very likely to take COVID-19 vaccines. Forty one percent (41%) showed no vaccine preference. Of the remaining 51% most preferred Pfizer. Data also suggest the likelihood of getting a COVID-19 vaccine was significantly correlated with concern about side effects, and attitude toward government vaccine guidelines. Males are more likely to be vaccinated than females. About the same percentage of students were likely or very likely to be vaccinated against COVID-19, regardless of whether they were vaccinated against the seasonal flu or not. It is comforting to see a majority of college students have taken some preventative measures against COVID-19. Keywords Novel Coronavirus, COVID-19

ABSTRACT This study briefly reviews the causes of the U.S.-China conflicts, the U.S. actions and China's responses. It continues to point out that China is not going to remove subsidies to SOEs, and 5G is critical in the development of cutting-edge technologies. As a result, the U.S.-China relations have entered into a new phase, a phase of prolonged fierce technological competition centered on 5G because dominance in the field of advanced technology will lead to dominance of the world. This paper discusses the U.S. campaign to constrain Huawei and lists possible causes for not being successful. This paper also reviews China's strong capabilities in high technology. The U.S. pressure on China, especially Executive Order 13873 and the Entity List, has forced China to start its nationwide campaign to be technologically independent. We posit that Beijing's directive, internally referred to as the “3-5-2” policy, issued in early 2019, and its intent to export its censored internet services may mark the starting point of the “Digital Great Wall”. Keywords Belt and Road Initiative; Chinese Dream; Entity List; Huawei; Long March; State-Owned Enterprise; 5G

With the proposal of intelligent high-speed railway, the research on remotely monitoring the intelligent traction substation becomes a key subject of high-speed railway safe operation. However, mosquitos adhered to the glass window or camera lens can severely hamper the visibility of a background scene, and degrade images considerably. Therefore, we propose a single image mosquito streaks removal method of high-speed railway traction substation based on the deep convolutional neural network. First, we employ guided filter to split input image into smoothing image and edge-preserving image. Then, the edge-preserving image is fed into our designed convolutional neural network to obtain learning map, which solves problems of background interference and focuses the model on the structure of rain streak in images, and the clean image is finally generated through adding the input image and learning map. The experiment results on Heishan traction substation real datasets show the effectiveness of our proposed method.

ABSTRACT In the classical Economic Order Quantity (EOQ) model, we assume that the planning horizon is infinite, and the parameters such as ordering and holding costs and demand rate are stationary or constant over the entire planning horizon. On the other hand, the Dynamic Lot Sizing (DLS) models described in the literature deal with a shorter horizon and parameter values changing from one period to the next. However, in practice, one would expect the parameter values to vary significantly if the planning horizon is relatively long, and to be relatively stable or constant, if it were shorter. With the adoption of supply chain management strategies and e-business technologies by many organizations in recent years, focus has shifted to shorter planning horizons. But only a few studies involving shorter horizons and stationary parameters have appeared in the literature. Even among them, each one deals with a special case involving combinations such as a finite production rate and no backlog or instantaneous replenishment with backlog, etc. Further, the algorithms described in these studies are not as simple or computationally as efficient as the classical EOQ formula. In this paper, a comprehensive version of these finite horizon inventory models is considered and an optimization algorithm that compares favorably with the classical EOQ formula in terms of simplicity and computational efficiency is presented for solving the several variants of the problem. Keywords EOQ model, Economic Order Quantity, Optimal Lot Sizing, Supply Chain Management

The spectral property of the Laplace-Beltrami operator has become relevant in shape analysis. One of the numerous methods that employ the strength of Laplace-Beltrami operator eigen-properties in shape analysis is the spectral multidimensional scaling which maps the MDS problem into the eigenspace of its Laplace-Beltrami operator. Using the biharmonic distance we show a further reduction in the complexities of the canonical form of shapes making similarities and dissimilarities of isometric shapes more efficiently computed. With the theoretical sound biharmonic distance we embed the intrinsic property of a given shape into a Euclidean metric space. Utilizing the farthest-point sampling strategy to select a subset of sampled points, we combine the potency of the spectral multidimensional scaling with global awareness of the biharmonic distance operator to propose an approach which embeds canonical forms images that shows further "resemblance" between isometric shapes. Experimental result shows an efficient and effective approximation with both distinctive local features and yet a robust global property of both the model and probe shapes. In comparison to a recent state-of-the-art work, the proposed approach can achieve comparable or even better results and have practical computational efficiency as well.

The primary goal of this paper is to provide insight into the causes that led to the current U.S. - China trade war. It discusses the importance of the 'Belt and Road Initiative' and the 'Made in China 2025' programs to Beijing's realization of the 'Chinese dream', which refers to the avoidance of the middle-income trap and the accomplishment of the nation's great rejuvenation. This paper points out the leading roles played by the state-owned enterprises in the above two programs and reviews their destabilizing effects on the Chinese society. This paper also describes the measures taken by the U.S. to counter China's efforts to become the new superpower, thereby preserving its preeminent position in the world. In addition, the paper discusses the steps taken by Beijing to try to satisfy Washington's demand. The authors posit that the trade war is not, in fact, about trade but about technological dominance, and that both sides might fall into 'Thucydides's Trap,' the pattern of large-scale conflict when a rising power challenges a dominant one. According to the events that have transpired thus far, it appears our current trajectory is towards conflict and a cold war