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As people become more aware of environmental issues, Tesla, a pillar of the global electric vehicle market, has become a hot commodity in recent years. The prediction of Tesla's share price is also a hot topic in the investment market. This experiment extracts sentiment factors of tweets about Tesla's comments, combined with Tesla's historical stock price as the dataset for training, testing and inspection. This experiment builds time series prediction models based on LSTM, XGBoost and RF algorithms to predict Tesla's stock price, and evaluates the prediction effectiveness of the three algorithms based on the fit and error of the prediction results. The analysis of the data shows that XGBoost has the best fit and the lowest error among the three algorithms, and that the sentiment factor has its unique utility as raw data. The experimental results also empirically demonstrate the applicability of sentiment factor analysis and the three algorithms LSTM, XGBoost and RF in the field of stock price prediction. [ABSTRACT FROM AUTHOR]

Contaminated water has remained an unsolved problem for decades, particularly when the contamination derived from heavy metals. A possible solution is to mix the contaminated water with magnetic nanoparticles so that an adsorption process can take place. In that frame, Tesla valve micromixer and Fe 3 O 4 magnetic nanoparticles were selected to perform simulations for encounter maximum mixing efficiency. These simulations focus on inlet velocities ratios between contaminated water and nanoparticles and inlet rates of nanoparticles. The maximum mixing efficiency was 44% for the inverse double Tesla micromixer found for the combination of Fe 3 O 4 nanoparticles as the inlet rate and with inlet velocity ratios of V p V c = 10 . [ABSTRACT FROM AUTHOR]

This research presents society's perceptions of Tesla through comments from the videos on their official YouTube channel. This research is focused on the perceptions of society through comments sections from four different videos. This research uses Poststructuralism as an approach that is supported by deconstruction theory by Derrida. From the deconstruction theory, this research employs the concept of difference to find out about many perceptions of Tesla in society. This research applies a qualitative descriptive technique, in which the author reports and analyses existing data. The data is taken from the comment section of four different videos from Tesla's YouTube channel. From analyzing the data relating to the theory, it is found that Tesla has several perceptions in society which are that Tesla is a high-tech innovation, Tesla is environmentally friendly, Tesla is expensive, Tesla is high-maintainable, and Tesla is a family car. These new perspectives show that the car has been accepted into society and plays a significant role in society. [ABSTRACT FROM AUTHOR]

A science writer who has been covering advanced technology for over 40 years gives a different, rarely seen view of tech startups: how they work, the common problems they seem to encounter – and why there are so many "Valley of Death" pitfalls waiting for them. [ABSTRACT FROM AUTHOR]

Objective: This study uses a detection task to measure changes in driver vigilance when operating four different partially automated systems. Background: Research show temporal declines in detection task performance during manual and fully automated driving, but the accuracy of using this approach for measuring changes in driver vigilance during on-road partially automated driving is yet unproven. Method: Participants drove four different vehicles (Tesla Model 3, Cadillac CT6, Volvo XC90, and Nissan Rogue) equipped with level-2 systems in manual and partially automated modes. Response times to a detection task were recorded over eight consecutive time periods. Results: Bayesian analysis revealed a main effect of time period and an interaction between mode and time period. A main effect of vehicle and a time period x vehicle interaction were also found. Conclusion: Results indicated that the reduction in detection task performance over time was worse during partially automated driving. Vehicle-specific analysis also revealed that detection task performance changed across vehicles, with slowest response time found for the Volvo. Application: The greater decline in detection performance found in automated mode suggests that operating level-2 systems incurred in a greater vigilance decrement, a phenomenon that is of interest for Human Factors practitioners and regulators. We also argue that the observed vehicle-related differences are attributable to the unique design of their in-vehicle interfaces. [ABSTRACT FROM AUTHOR]

Watermarking signal authentication is a technique in which a global navigation satellite system (GNSS) provider cryptographically perturbs the spreading code to allow for limited cryptographic authentication of a signal. Several proposals and studies have been presented or are underway to augment GNSS signals with this capability. This work reintroduces a generalized combinatorial watermarking function that affords a flexible pathway to cryptographically prove the authentication security of a signal with receiver observables under certain assumptions. The security levels are comparable to those of standard cryptographic security (e.g., 128-bit security) and require little or no additional use of the navigation data bandwidth. We show how our methods can be applied to signals of different designs and signal-to-noise ratios. With our receiver processing strategy, one can design a watermarking signal authentication scheme and the accompanying receiver to have high confidence in a signal's authenticity. [ABSTRACT FROM AUTHOR]

This article examines the rise and recent decline of Tesla in the U.S. electric vehicle market. Using qualitative, semi-quantitative, and statistical methods, the article traces how Tesla acquired a first-mover advantage and how second movers, both established automakers and start-ups, responded to Tesla’s rise. The recent decline in Tesla’s share of the U.S. electric vehicle market is linked to several factors: the proliferation of electric vehicle offerings from competitors, changes in public policy, and controversial decisions by Tesla and its CEO. The article concludes with a discussion of promising future strategies for both Tesla and its competitors.

Human geographers are increasingly concerned with how 'futures' are imagined and rendered governable, yet mostly their methods lack the sensitivity to explore the functioning of complex relations between heterogeneous actors across places. The world's electric vehicle (EV) sector is booming, presaging a widely expected decarbonised future, associated with a restructuring of the automobile industry as anticipated by proactive players. This paper interrogates the spatiality and politics of the EV future‐making through disentangling the translocal practices involved in realising Tesla's Gigafactory in Shanghai (TGS) as assemblage. Informed by interviews with industrial insiders and opensource information in Chinese and English, the article finds that, first, TGS's imagined future embodies a multiplicity of interdependent but divergent expectations, the coherence of which underlies the formation and operation of the TGS assemblage by virtue of the concerted actions of its member‐actors. Second, such coherence is conditional as designed by TGS's central planners—namely, Tesla and Chinese government agencies at central and local levels—for their differentiated but overlapping interests. The TGS's imagined future is rendered actionable, enrolling other agents at certain moments, through anticipatory practices of regulatory changes, strategic arrangements interweaving land and financing, firm acquisition and intra‐firm reorganisation linking up places in and outside China, as well as the selection of key suppliers and technological use of critical raw materials. Concluding after a sketch on the TGS's 'possible futures' and broader implications, the paper contributes an assemblage‐informed approach to disentangle futuremaking practices and generates timely insights into the 'future‐oriented' restructuring of the automobile industry. [ABSTRACT FROM AUTHOR]

A small-scale experimental set-up was designed and built, consisting of a Tesla turbine and electric generator, with casing, consumer and measurement devices. Experimental measurements were carried out, regarding the working performance of the turbine at different air inlet pressures. The other parameters measured were the inlet air velocity, the rotational speed and the output electrical power. The results were discussed and explained through graphs, and conclusions were drawn. [ABSTRACT FROM AUTHOR]

To design relevant policy measures and incentives to accelerate the uptake of electric vehicles in Australia, it is important to understand who the early adopters of electric vehicles are, their reasons for choosing an electric vehicle and their levels of satisfaction in driving, charging locations, home charging and other experiences. This article presents the results of a survey of early adopters in Queensland, Australia. The data have been analysed to understand the socio-demographic profiles of early adopters and to explore variations between two groups of adopters: Tesla owners, having the highest uptake of battery electric vehicles in Australia, and non-Tesla owners of battery electric vehicles and plug-in hybrid electric vehicles. The analysis suggests that both groups of early adopters are predominantly male, university educated and have substantially higher incomes than the state average. Peer and media influences, and having a test drive, play a significant role in owning a Tesla. [ABSTRACT FROM AUTHOR]

Problem definition: We estimate the impact of electric vehicle (EV) charging stations on volumes of consumer foot traffic received by nearby retail establishments. We also explore the conditions under which any effects manifest. Methodology/results: We use a differences-in-differences design, exploiting the staggered introduction of Tesla Supercharger stations across the United States. We combine data on Supercharger installations with mobile phone–based estimates of retailer foot traffic. We explore heterogeneity in the treatment effect, in terms of EV charger characteristics, visitor characteristics, establishment type, and local physical context. We estimate that establishments experience an average 4% increase in monthly visits following the installation of a Tesla Supercharger. These effects arise primarily for retailers that offer relatively quick services (e.g., fast food) and for those located very near to the charger (within 150 meters). The effects are also more pronounced when the Supercharger is one of the first EV chargers introduced into the local area. Managerial implications: We document evidence of the positive retail demand spillovers arising from EV charging station infrastructure. We also document the conditions under which the benefits manifest. Insights for EV network operators, retailers, and policymakers are included. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0519. [ABSTRACT FROM AUTHOR]

The purpose of the paper is to develop a strategy to increase the competitiveness of Tesla's electric car in the market, including an analysis of possible competitors, identifying the strengths and weaknesses of the company, identifying opportunities for improvement and formulating recommendations for further development. It is proven that people are increasingly choosing environmentally friendly vehicles that use alternative energy sources. It was found that one of the leaders in the electric car segment is "Tesla". By releasing new models, Tesla has repeatedly changed the rules of the game in the electric vehicle market, taking leading positions in all ratings. Research methodology. To achieve this goal, the method of analysis and synthesis, the method of statistical analysis of indicators, the method of theoretical generalisation and methods of economic analysis were used. The main advantages and disadvantages of electric vehicles, in particular the Tesla car, are investigated. The strengths and weaknesses, internal resources and capabilities of Tesla and its main competitors are analysed using SWOT analysis, VRIO analysis and Porter's 5 forces analysis. The analysis showed that Tesla has several strengths, such as the production of its own components, direct sales to customers and a strong brand. However, frequent production delays, a high-price strategy, and limited production volume pose challenges for the company. It is determined that an influential figure for the tesla brand is the eccentric and widely known public image of Elon Musk. The total sales of electric vehicles are also analysed and Tesla's main competitor is identified. The results of the study show that there is a great deal of competition in the electric vehicle market, which emphasises the need for Tesla to actively develop and update its strategy. Priority areas for improving the competitiveness of the Tesla electric vehicle are proposed. In particular, it was proposed to: expand the network of charging stations and improve the navigation system; reduce maintenance costs and offer more affordable prices; expand production capacity; obtain permission to install turquoise warning lights on its cars; improve the autopilot function; continue to create exquisite car designs that will be different from others.

Contaminated water has remained an unsolved problem for decades, particularly when the contamination derived from heavy metals. A possible solution is to mix the contaminated water with magnetic nanoparticles so that an adsorption process can take place. In that frame, Tesla valve micromixer and Fe3O4 magnetic nanoparticles were selected to perform simulations for encounter maximum mixing efficiency. These simulations focus on inlet velocities ratios between contaminated water and nanoparticles and inlet rates of nanoparticles. The maximum mixing efficiency was 44% for the inverse double Tesla micromixer found for the combination of Fe3O4 nanoparticles as the inlet rate and with inlet velocity ratios of VpVc=10.

We study the impact of Tesla's entry on China's electric vehicle (EV) market. We find that Tesla's entry has substantially increased the demand for EVs in China, and therefore has benefited Chinese EV producers. However, we also find that this positive impact was nullified for local EV producers that compete with Tesla in a more head-to-head manner, and those that compete in markets that host Tesla Galleries and have a higher annual income per capita. Moreover, local manufacturers lowered their EV prices when faced with competition from domestically produced Tesla vehicles, and the magnitude of such price reductions was larger for battery electric vehicle (BEV) models. [ABSTRACT FROM AUTHOR]

SBAS is mainly used in civil aviation and navigation, and will be applied to autonomous driving in the future. Given the open signal format of the Satellite Based Augmentation System (SBAS), which exposes security threats such as spoofing attacks, the utilization of SBAS navigation message authentication technology can improve the SBAS anti-spoofing ability from the system side. SBAS message authentication technology has become the future direction of SBAS system development. However, during the initial design of SBAS on L1, message authentication technology was not considered, and the addition of authentication messages will lead to further strain on existing message bandwidth resources. Therefore, in response to the issue of insufficient bandwidth resources after adding authentication messages to SBAS L1, a study on message scheduler for SBAS L1 authentication was conducted. A fixed time sequence dynamic message scheduler for incorporating authentication messages was proposed. This scheduler reduces the frequency of broadcasting clock error parameters to mitigate the impact of adding authentication messages. Furthermore, an optimized fixed time sequence dynamic message scheduler based on SBAS clock error messages was introduced. The results show that the message scheduler can not only improve the flexibility of SBAS message broadcasting, but also shorten the update interval of various types of messages under the premise of meeting the maximum update interval requirement. With minimal impact on the maximum message update interval, it improves the integrity, authenticity, and availability of messages. This approach can increase the effective message ratio in SBAS to over 91%, and the optimal solution reduces the initial user positioning time to 26 s. [ABSTRACT FROM AUTHOR]

Identification of proteoforms, the different forms of a protein, is important to understand biological processes. A proteoform family is the set of different proteoforms from the same gene. We previously developed the software program Proteoform Suite, which constructs proteoform families and identifies proteoforms by intact-mass analysis. Here, we have applied this approach to top-down proteomic data acquired at the National High Magnetic Field Laboratory 21 tesla Fourier transform ion cyclotron resonance mass spectrometer (data available on the MassIVE platform with identifier MSV000085978). We explored the ability to construct proteoform families and identify proteoforms from the high mass accuracy data that this instrument provides for a complex cell lysate sample from the MCF-7 human breast cancer cell line. There were 2830 observed experimental proteforms, of which 932 were identified, 44 were ambiguous, and 1854 were unidentified. Of the 932 unique identified proteoforms, 766 were identified by top-down MS2 analysis at 1% false discovery rate (FDR) using TDPortal, and 166 were additional intact-mass identifications (∼4.7% calculated global FDR) made using Proteoform Suite. We recently published a proteoform level schema to represent ambiguity in proteoform identifications. We implemented this proteoform level classification in Proteoform Suite for intact-mass identifications, which enables users to determine the ambiguity levels and sources of ambiguity for each intact-mass proteoform identification.

Summary: Individuals with telomere biology disorders (TBDs) have very short telomeres, high risk of bone marrow failure (BMF), and reduced survival. Using data from TBD patients, a mean leukocyte Southern blot telomere length (TL) of 5 kilobases (kb) was estimated as the 'telomere brink' at which human survival is markedly reduced. However, the shortest telomere, not the mean TL, signals replicative senescence. We used the Telomere Shortest Length Assay (TeSLA) to tally TL of all 46 chromosomes in blood‐derived DNA and examined its relationship with TBDs. Patients (n = 18) had much shorter mean TL (TeSmTL) (2.54 ± 0.41 kb vs. 4.48 ± 0.52 kb, p < 0.0001) and more telomeres <3 kb than controls (n = 22) (70.43 ± 8.76% vs. 33.05 ± 6.93%, p < 0.0001). The proportion of ultrashort telomeres (<1.6 kb) was also higher in patients than controls (39.29 ± 10.69% vs. 10.40 ± 4.09%, p < 0.0001). TeS <1.6 kb was associated with severe (n = 11) compared with non‐severe (n = 7) BMF (p = 0.027). Patients with multi‐organ manifestations (n = 10) had more telomeres <1.6 kb than those with one affected organ system (n = 8) (p = 0.029). Findings suggest that TBD clinical manifestations are associated with a disproportionately higher number of haematopoietic cell telomeres reaching a telomere brink, whose length at the single telomere level is yet to be determined. [ABSTRACT FROM AUTHOR]

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community.

Here we delineate a complete satellite-based augmentation system (SBAS) authentication scheme, including over-the-air rekeying (OTAR), that uses the elliptic curve digital signature algorithm (ECDSA) and timed efficient stream loss-tolerant authentication (TESLA) without the quadrature (Q) channel. This scheme appends two new message types to the SBAS scheduler without overburdening the message schedule. We have taken special care to ensure that our scheme (1) meets the appropriate security requirements needed to prevent and deter spoofing; (2) is compatible with existing cryptographic standards; (3) is flexible, expandable, and future-proof to different cryptographic and implementation schemes; and (4) is backward compatible with legacy receivers. The scheme accommodates a diverse set of features, including authenticating core-constellation ephemerides. We discuss the SBAS provider and receiver machine state and its startup, including its use by aircraft that traverse differing SBAS coverage areas. We tested our scheme with existing SBAS simulation and analysis tools and found that it had negligible effects on current SBAS availability and continuity requirements. [ABSTRACT FROM AUTHOR]

Conflicts are considered as vital elements of plural democracies in agonistic political and planning theory. According to this theory, antagonisms are to be tamed and channeled into agonistic disputes. Therefore, forms of participation in planning procedures play a key role in the resolution and regulation of conflicts. The central question of this paper is the role of participatory procedures in planning in order to resolve and settle conflicts, which occur in a particularly sharp way in the context of large-scale projects. The paper presents planning conflicts and forms of participation using the case of the settlement of the Gigafactory Tesla in the German state of Brandenburg. Within the framework of an empirical case study, the approval procedure of the project and a land use plan procedure of the municipality are analysed. Both procedures are characterized by a great acceleration, early preliminary decisions and participation deficits. The result shows that in the case of the settlement of Tesla, in addition to conflicts of interest, values and location, procedural conflicts also occur, which call the acceptance of planning into question. The forms of participation practiced do not prove suitable for taming conflicts, but rather produce mistrust among opponents and reinforce antagonistic dynamics. [ABSTRACT FROM AUTHOR]

Distributed neural network computation heavily relies on GPUs and high-speed interconnects. We use Nvidia Tesla GPUs with Angara interconnect for distributed deep learning. We present early performance evaluation results of the Angara interconnect software stack with Nvidia GPU support. We compare the training performance of ResNet50, ResNet152, and DenseNet201 neural networks from the TensorFlow framework when using Nvidia V100 GPUs with Angara, Nvidia Infiniband EDR 56 Gbit/s, and 1 Gbit/s Ethernet interconnects. [ABSTRACT FROM AUTHOR]