Search

Embodied AI robots have the potential to fundamentally improve the way human beings live and manufacture. Continued progress in the burgeoning field of using large language models to control robots depends critically on an efficient computing substrate. In particular, today's computing systems for embodied AI robots are designed purely based on the interest of algorithm developers, where robot actions are divided into a discrete frame-basis. Such an execution pipeline creates high latency and energy consumption. This paper proposes Corki, an algorithm-architecture co-design framework for real-time embodied AI robot control. Our idea is to decouple LLM inference, robotic control and data communication in the embodied AI robots compute pipeline. Instead of predicting action for one single frame, Corki predicts the trajectory for the near future to reduce the frequency of LLM inference. The algorithm is coupled with a hardware that accelerates transforming trajectory into actual torque signals used to control robots and an execution pipeline that parallels data communication with computation. Corki largely reduces LLM inference frequency by up to 8.0x, resulting in up to 3.6x speed up. The success rate improvement can be up to 17.3%. Code is provided for re-implementation. https://github.com/hyy0613/Corki

Deuterium fractionation in the closest vicinity of a protostar is important in understanding its potential heritage to a planetary system. Here, we have detected the spectral line emission of CH3OH and its three deuterated species, CH2DOH, CHD2OH, and CH3OD, toward the low-mass protostellar source B335 at a resolution of 0.''03 (5 au) with Atacama Large Millimeter/submillimeter Array. They have a ring distribution within the radius of 24 au with the intensity depression at the continuum peak. We derive the column densities and abundance ratios of the above species at 6 positions in the disk/envelope system as well as the continuum peak. The D/H ratio of CH3OH is ~[0.03-0.13], which is derived by correcting the statistical weight of 3 for CH2DOH. The [CHD2OH]/[CH2DOH] ratio is derived to be higher ([0.14-0.29]). On the other hand, the [CH2DOH]/[CH3OD] ratio ([4.9-15]) is higher than the statistical ratio of 3, and is comparable to those reported for other low-mass sources. We study the physical structure on a few au scale in B335 by analyzing the CH3OH (183,15-182,16, A) and HCOOH (120,12-110,11) line emission. Velocity structures of these lines are reasonably explained as the infalling-rotating motion. The protostellar mass and the upper limit to centrifugal barrier are thus derived to be 0.03-0.07 M_{\odot} and <7 au, respectively, showing that B335 harbors a young protostar with a tiny disk structure. Such youth of the protostar may be related to the relatively high [CH2DOH]/[CH3OH] ratio.

We report the first detection in the interstellar medium of $N$-cyanomethanimine (H$_2$CNCN), the stable dimer of HCN of highest energy, and the most complex organic molecule identified in space containing the prebiotically relevant NCN backbone. We have identified a plethora of $a$-type rotational transitions with 3 $\leq J_\text{up} \leq$ 11 and $K_\text{a} \leq$ 2 that belong to this species towards the Galactic Center G+0.693-0.027 molecular cloud, the only interstellar source showing the three cyanomethanimine isomers (including the $Z$- and $E$- isomers of $C$-cyanomethanimine, HNCHCN). We have derived a total column density for H$_2$CNCN of (2.9$\, \pm \,$0.1)$\times$10$^{12}$ cm$^{-2}$, which translates into a total molecular abundance with respect to H$_2$ of (2.1$\, \pm \,$0.3)$\times$10$^{-11}$. We have also revisited the previous detection of $E$- and $Z$-HNCHCN, and found a total $C/N$-cyanomethanimine abundance ratio of 31.8$\, \pm \,$1.8 and a $Z/E$-HNCHCN ratio of 4.5$\, \pm \,$0.2. While the latter can be explained on the basis of thermodynamic equilibrium, chemical kinetics are more likely responsible for the observed $C/N$-cyanomethanimine abundance ratio, where the gas-phase reaction between methanimine (CH$_2$NH) and the cyanogen radical (CN) arises as the primary formation route., Comment: 22 pages, 8 figures, 3 tables, 2 appendix - Accepted for publication in The Astrophysical Journal

We present the first detection in space of thionylimide (HNSO) toward the Galactic Center molecular cloud G+0.693-0.027, thanks to the superb sensitivity of an ultradeep molecular line survey carried out with the Yebes 40$\,$m and IRAM 30$\,$m telescopes. This molecule is the first species detected in the interstellar medium containing, simultaneously, N, S and O. We have identified numerous $K$$_a$ = 0, 1 and 2 transitions belonging to HNSO covering from $J$$_{\rm up}$ = 2 to $J$$_{\rm up}$ = 10, including several completely unblended features. We derive a molecular column density of $N$ = (8 $\pm$ 1)$\times$10$^{13}$ cm$^{-2}$, yielding a fractional abundance relative to H$_2$ of $\sim$6$\times$10$^{-10}$, which is about $\sim$37 and $\sim$4.8 times less abundant than SO and SO2, respectively. Although there are still many unknowns in the interstellar chemistry of NSO-bearing molecules, we propose that HNSO is likely formed through the reaction of the NSO radical and atomic H on the surface of icy grains, with alternative routes also deserving exploration. Finally, HNSO appears as a promising link between N- , S- and O- interstellar chemistry and its discovery paves the route to the detection of a new family of molecules in space., Comment: Forthcoming paper in The Astrophysical Journal Letters (in press)

This study unveils the In-Context Evolutionary Search (ICE-SEARCH) method, which is among the first works that melds large language models (LLMs) with evolutionary algorithms for feature selection (FS) tasks and demonstrates its effectiveness in Medical Predictive Analytics (MPA) applications. ICE-SEARCH harnesses the crossover and mutation capabilities inherent in LLMs within an evolutionary framework, significantly improving FS through the model's comprehensive world knowledge and its adaptability to a variety of roles. Our evaluation of this methodology spans three crucial MPA tasks: stroke, cardiovascular disease, and diabetes, where ICE-SEARCH outperforms traditional FS methods in pinpointing essential features for medical applications. ICE-SEARCH achieves State-of-the-Art (SOTA) performance in stroke prediction and diabetes prediction; the Decision-Randomized ICE-SEARCH ranks as SOTA in cardiovascular disease prediction. The study emphasizes the critical role of incorporating domain-specific insights, illustrating ICE-SEARCH's robustness, generalizability, and convergence. This opens avenues for further research into comprehensive and intricate FS landscapes, marking a significant stride in the application of artificial intelligence in medical predictive analytics.

We present the first detection in space of O-protonated carbonyl sulfide (\ch{HOCS+}), in the midst of an ultradeep molecular line survey toward the G+0.693-0.027 molecular cloud. From the observation of all $K$$_a$ = 0 transitions ranging from $J$$_{lo}$ = 2 to $J$$_{lo}$ = 13 of \ch{HOCS+} covered by our survey, we derive a column density of $N$ = (9 $\pm$ 2)$\times$10$^{12}$ cm$^{-2}$, translating into a fractional abundance relative to H$_2$ of $\sim$7$\times$10$^{-11}$. Conversely, the S-protonated \ch{HSCO+} isomer remains undetected, and we derive an upper limit to its abundance with respect to H$_2$ of $\leq$3$\times$10$^{-11}$, a factor of $\geq$2.3 less abundant than \ch{HOCS+}. We obtain a \ch{HOCS+}/OCS ratio of $\sim$2.5$\times$10$^{-3}$, in good agreement with the prediction of astrochemical models. These models show that one of the main chemical routes to the interstellar formation of \ch{HOCS+} is likely the protonation of OCS, which appears to be more efficient at the oxygen end. Also, we find that high values of cosmic-ray ionisation rates (10$^{-15}$-10$^{-14}$ s$^{-1}$) are needed to reproduce the observed abundance of \ch{HOCS+}. In addition, we compare the O/S ratio across different interstellar environments. G+0.693-0.027 appears as the source with the lowest O/S ratio. We find a \ch{HOCO+}/\ch{HOCS+} ratio of $\sim$31, in accordance with other O/S molecular pairs detected toward this region and also close to the O/S solar value ($\sim$37). This fact indicates that S is not significantly depleted within this cloud due to the action of large-scale shocks, unlike in other sources where S-bearing species remain trapped on icy dust grains., Comment: Forthcoming paper in The Astrophysical Journal (in press)

Due to the cultural and governance differences of countries around the world, there currently exists a wide spectrum of AI regulation policy proposals that have created a chaos in the global AI regulatory space. Properly regulating AI technologies is extremely challenging, as it requires a delicate balance between legal restrictions and technological developments. In this article, we first present a comprehensive review of AI regulation proposals from different geographical locations and cultural backgrounds. Then, drawing from historical lessons, we develop a framework to facilitate a thorough analysis of AI regulation proposals. Finally, we perform a systematic analysis of these AI regulation proposals to understand how each proposal may fail. This study, containing historical lessons and analysis methods, aims to help governing bodies untangling the AI regulatory chaos through a divide-and-conquer manner.

We report the first detection in the interstellar medium of a C$_2$H$_5$O$_2$N isomer: $syn$-glycolamide (NH$_2$C(O)CH$_2$OH). The exquisite sensitivity at sub-mK levels of an ultra-deep spectral survey carried out with the Yebes 40m and IRAM 30m telescopes towards the G+0.693-0.027 molecular cloud have allowed us to unambiguously identify multiple transitions of this species. We derived a column density of (7.4 $\pm$ 0.7)$\times$10$^{12}$ cm$^{-2}$, which implies a molecular abundance with respect to H$_2$ of 5.5$\times$10$^{-11}$. The other C$_2$H$_5$O$_2$N isomers, including the higher-energy $anti$ conformer of glycolamide, and two conformers of glycine, were not detected. The upper limit derived for the abundance of glycine indicates that this amino acid is surely less abundant than its isomer glycolamide in the ISM. The abundances of the C$_2$H$_5$O$_2$N isomers cannot be explained in terms of thermodynamic equilibrium, and thus chemical kinetics need to be invoked. While the low abundance of glycine might not be surprising, based on the relative low abundances of acids in the ISM compared to other compounds (e.g. alcohols, aldehydes or amines), several chemical pathways can favour the formation of its isomer glycolamide. It can be formed through radical-radical reactions on the surface of dust grains. The abundances of these radicals can be significantly boosted in an environment affected by a strong ultraviolet field induced by cosmic rays, such as that expected in G+0.693-0.027. Therefore, as shown by several recent molecular detections towards this molecular cloud, it stands out as the best target to discover new species with carbon, oxygen and nitrogen with increasing chemical complexity., Comment: Accepted in The Astrophysical Journal Letters

After a quarter century since the detection of the last interstellar carboxylic acid, acetic acid (CH$_3$COOH), we report the discovery of a new one, the cis-trans form of carbonic acid (HOCOOH), toward the Galactic Center molecular cloud G+0.693-0.027. HOCOOH stands as the first interstellar molecule containing three oxygen atoms and also the third carboxylic acid detected so far in the interstellar medium. Albeit the limited available laboratory measurements (up to 65 GHz), we have also identified several pairs of unblended lines directly in the astronomical data (between 75-120 GHz), which allowed us to slightly improve the set of spectroscopic constants. We derive a column density for cis-trans HOCOOH of $N$ = (6.4 $\pm$ 0.4) $\times$ 10$^{12}$ cm$^{-2}$, which yields an abundance with respect to molecular H$_2$ of 4.7 $\times$ 10$^{-11}$. Meanwhile, the extremely low dipole moment (about fifteen times lower) of the lower-energy conformer, cis-cis HOCOOH, precludes its detection. We obtain an upper limit to its abundance with respect to H$_2$ of $\leq$ 1.2 $\times$10$^{-9}$, which suggests that cis-cis HOCOOH might be fairly abundant in interstellar space, although it is nearly undetectable by radio astronomical observations. We derive a cis-cis/cis-trans ratio $\leq$ 25, consistent with the smaller energy difference between both conformers compared with the relative stability of trans- and cis-formic acid (HCOOH). Finally, we compare the abundance of these acids in different astronomical environments, further suggesting a relationship between the chemical content found in the interstellar medium and the chemical composition of the minor bodies of the Solar System, which could be inherited during the star formation process., Comment: Accepted for publication in The Astrophysical Journal

With the advancement of robotics and AI technologies in the past decade, we have now entered the age of autonomous machines. In this new age of information technology, autonomous machines, such as service robots, autonomous drones, delivery robots, and autonomous vehicles, rather than humans, will provide services. In this article, through examining the technical challenges and economic impact of the digital economy, we argue that scalability is both highly necessary from a technical perspective and significantly advantageous from an economic perspective, thus is the key for the autonomy industry to achieve its full potential. Nonetheless, the current development paradigm, dubbed Autonomy 1.0, scales with the number of engineers, instead of with the amount of data or compute resources, hence preventing the autonomy industry to fully benefit from the economies of scale, especially the exponentially cheapening compute cost and the explosion of available data. We further analyze the key scalability blockers and explain how a new development paradigm, dubbed Autonomy 2.0, can address these problems to greatly boost the autonomy industry.

This paper introduces Artificial Intelligence Clinics on Mobile (AICOM), an open-source project devoted to answering the United Nations Sustainable Development Goal 3 (SDG3) on health, which represents a universal recognition that health is fundamental to human capital and social and economic development. The core motivation for the AICOM project is the fact that over 80% of the people in the least developed countries (LDCs) own a mobile phone, even though less than 40% of these people have internet access. Hence, through enabling AI-based disease diagnostics and screening capability on affordable mobile phones without connectivity will be a critical first step to addressing healthcare access problems. The technologies developed in the AICOM project achieve exactly this goal, and we have demonstrated the effectiveness of AICOM on monkeypox screening tasks. We plan to continue expanding and open-sourcing the AICOM platform, aiming for it to evolve into an universal AI doctor for the Underserved and Hard-to-Reach.

The ${\rm H_2NC}$ radical is the high-energy metastable isomer of ${\rm H_2CN}$ radical, which has been recently detected for the first time in the interstellar medium towards a handful of cold galactic sources, besides a warm galaxy in front of the PKS 1830-211 quasar. These detections have shown that the ${\rm H_2CN}$/${\rm H_2NC}$ isomeric ratio, likewise the HCN/HNC ratio, might increase with the kinetic temperature ($T_{\rm kin}$), but the shortage of them in warm sources still prevents us to confirm this hypothesis and shed light about their chemistry. In this work, we present the first detection of ${\rm H_2CN}$ and ${\rm H_2NC}$ towards a warm galactic source, the G+0.693-0.027 molecular cloud (with $T_{\rm kin} > 70 \, {\rm K}$), using IRAM 30m observations. We have detected multiple hyperfine components of the $N_{K_\text{a}K_\text{c}} = 1_{01} - 0_{00}$ and $2_{02} - 1_{01}$ transitions. We derived molecular abundances with respect to ${\rm H_2}$ of (6.8$\pm$1.3)$\times 10^{-11}$ for ${\rm H_2CN}$ and of (3.1$\pm$0.7)$\times 10^{-11}$ for ${\rm H_2NC}$, and a ${\rm H_2CN}$/${\rm H_2NC}$ abundance ratio of 2.2$\pm$0.5. These detections confirm that the ${\rm H_2CN}$/${\rm H_2NC}$ ratio is $\gtrsim$2 for sources with $T_{\rm kin} > 70 \, {\rm K}$, larger than the $\sim$1 ratios previously found in colder cores ($T_{\rm kin}\sim10 \, {\rm K}$). This isomeric ratio dependence with temperature cannot be fully explained with the currently proposed gas-phase formation and destruction pathways. Grain surface reactions, including the ${\rm H_2NC} \rightarrow {\rm H_2CN}$ isomerization, deserve consideration to explain the higher isomeric ratios and ${\rm H_2CN}$ abundances observed in warm sources, where the molecules can be desorbed into the gas phase through thermal and/or shock-induced mechanisms., Comment: 12 pages, 5 figures, 3 tables, 2 appendix - Accepted for publication in Monthly Notices of the Royal Astronomical Society

While Artificial Intelligence (AI) technologies are progressing fast, compliance costs have become a huge financial burden for AI startups, which are already constrained on research & development budgets. This situation creates a compliance trap, as many AI startups are not financially prepared to cope with a broad spectrum of regulatory requirements. Particularly, the complex and varying regulatory processes across the globe subtly give advantages to well-established and resourceful technology firms over resource-constrained AI startups [1]. The continuation of this trend may phase out the majority of AI startups and lead to giant technology firms' monopolies of AI technologies. To demonstrate the reality of the compliance trap, from a field deployment perspective, we delve into the details of compliance costs of AI commercial operations.

As Deep Neural Networks (DNNs) are increasingly deployed in safety critical and privacy sensitive applications such as autonomous driving and biometric authentication, it is critical to understand the fault-tolerance nature of DNNs. Prior work primarily focuses on metrics such as Failures In Time (FIT) rate and the Silent Data Corruption (SDC) rate, which quantify how often a device fails. Instead, this paper focuses on quantifying the DNN accuracy given that a transient error has occurred, which tells us how well a network behaves when a transient error occurs. We call this metric Resiliency Accuracy (RA). We show that existing RA formulation is fundamentally inaccurate, because it incorrectly assumes that software variables (model weights/activations) have equal faulty probability under hardware transient faults. We present an algorithm that captures the faulty probabilities of DNN variables under transient faults and, thus, provides correct RA estimations validated by hardware. To accelerate RA estimation, we reformulate RA calculation as a Monte Carlo integration problem, and solve it using importance sampling driven by DNN specific heuristics. Using our lightweight RA estimation method, we show that transient faults lead to far greater accuracy degradation than what todays DNN resiliency tools estimate. We show how our RA estimation tool can help design more resilient DNNs by integrating it with a Network Architecture Search framework.

Under the Autonomous Mobile Clinics (AMCs) initiative, we are developing, open sourcing, and standardizing health AI technologies to enable healthcare access in least developed countries (LDCs). We deem AMCs as the next generation of health care delivery platforms, whereas health AI engines are applications on these platforms, similar to how various applications expand the usage scenarios of smart phones. Facing the recent global monkeypox outbreak, in this article, we introduce AICOM-MP, an AI-based monkeypox detector specially aiming for handling images taken from resource-constrained devices. Compared to existing AI-based monkeypox detectors, AICOM-MP has achieved state-of-the-art (SOTA) performance. We have hosted AICOM-MP as a web service to allow universal access to monkeypox screening technology. We have also open sourced both the source code and the dataset of AICOM-MP to allow health AI professionals to integrate AICOM-MP into their services. Also, through the AICOM-MP project, we have generalized a methodology of developing health AI technologies for AMCs to allow universal access even in resource-constrained environments.

Infrastructure-Vehicle Cooperative Autonomous Driving (IVCAD) is a new paradigm of autonomous driving, which relies on the cooperation between intelligent roads and autonomous vehicles. This paradigm has been shown to be safer and more efficient compared to the on-vehicle-only autonomous driving paradigm. Our real-world deployment data indicates that the effectiveness of IVCAD is constrained by reliability and performance of commercial communication networks. This paper targets this exact problem, and proposes INTERNEURON, a middleware to achieve high communication reliability between intelligent roads and autonomous vehicles, in the context of IVCAD. Specifically, INTERNEURON dynamically matches IVCAD applications and the underlying communication technologies based on varying communication performance and quality needs. Evaluation results confirm that INTERNEURON reduces deadline violations by more than 95\%, significantly improving the reliability of IVCAD systems.

Factor graph is a graph representing the factorization of a probability distribution function, and has been utilized in many autonomous machine computing tasks, such as localization, tracking, planning and control etc. We are developing an architecture with the goal of using factor graph as a common abstraction for most, if not, all autonomous machine computing tasks. If successful, the architecture would provide a very simple interface of mapping autonomous machine functions to the underlying compute hardware. As a first step of such an attempt, this paper presents our most recent work of developing a factor graph accelerator for LiDAR-Inertial Odometry (LIO), an essential task in many autonomous machines, such as autonomous vehicles and mobile robots. By modeling LIO as a factor graph, the proposed accelerator not only supports multi-sensor fusion such as LiDAR, inertial measurement unit (IMU), GPS, etc., but solves the global optimization problem of robot navigation in batch or incremental modes. Our evaluation demonstrates that the proposed design significantly improves the real-time performance and energy efficiency of autonomous machine navigation systems. The initial success suggests the potential of generalizing the factor graph architecture as a common abstraction for autonomous machine computing, including tracking, planning, and control etc., Comment: ICCAD 2022

One key technical challenge in the age of autonomous machines is the programming of autonomous machines, which demands the synergy across multiple domains, including fundamental computer science, computer architecture, and robotics, and requires expertise from both academia and industry. This paper discusses the programming theory and practices tied to producing real-life autonomous machines, and covers aspects from high-level concepts down to low-level code generation in the context of specific functional requirements, performance expectation, and implementation constraints of autonomous machines., Comment: EMSOFT 2022

This paper is the first to provide a thorough system design overview along with the fusion methods selection criteria of a real-world cooperative autonomous driving system, named Infrastructure-Augmented Autonomous Driving or IAAD. We present an in-depth introduction of the IAAD hardware and software on both road-side and vehicle-side computing and communication platforms. We extensively characterize the IAAD system in the context of real-world deployment scenarios and observe that the network condition that fluctuates along the road is currently the main technical roadblock for cooperative autonomous driving. To address this challenge, we propose new fusion methods, dubbed "inter-frame fusion" and "planning fusion" to complement the current state-of-the-art "intra-frame fusion". We demonstrate that each fusion method has its own benefit and constraint.

Nitriles play a key role as molecular precursors in prebiotic experiments based on the RNA-world scenario for the origin of life. These chemical compounds could have been partially delivered to the young Earth from extraterrestrial objects, stressing the importance of establishing the reservoir of nitriles in the interstellar medium. We report here the detection towards the molecular cloud G+0.693-0.027 of several nitriles, including cyanic acid (HOCN), and three C$_4$H$_3$N isomers (cyanoallene, CH$_2$CCHCN; propargyl cyanide, HCCCH$_2$CN; and cyanopropyne (CH$_3$CCCN), and the tentative detections of cyanoformaldehyde (HCOCN), and glycolonitrile (HOCH$_2$CN). We have also performed the first interstellar search of cyanoacetaldehyde (HCOCH$_2$CN), which was not detected. Based on the derived molecular abundances of the different nitriles in G+0.693-0.027 and other interstellar sources, we have discussed their formation mechanisms in the ISM. We propose that the observed HOCN abundance in G+0.693-0.027 is mainly due to surface chemistry and subsequent shock-induced desorption, while HCOCN might be mainly formed through gas-phase chemistry. In the case of HOCH$_2$CN, several grain-surface routes from abundant precursors could produce it. The derived abundances of the three C$_4$H$_3$N isomers in G+0.693-0.027 are very similar, and also similar to those previously reported in the dark cold cloud TMC-1. This suggests that the three isomers are likely formed through gas-phase chemistry from common precursors, possibly unsaturated hydrocarbons (CH$_3$CCH and CH$_2$CCH$_2$) that react with the cyanide radical (CN). The rich nitrile feedstock found towards G+0.693-0.027 confirms that interstellar chemistry is able to synthesize in space molecular species that could drive the prebiotic chemistry of the RNA-world., Comment: Accepted in Frontiers in Astronomy and Space Sciences

Robotic computing has reached a tipping point, with a myriad of robots (e.g., drones, self-driving cars, logistic robots) being widely applied in diverse scenarios. The continuous proliferation of robotics, however, critically depends on efficient computing substrates, driven by real-time requirements, robotic size-weight-and-power constraints, cybersecurity considerations, and dynamically changing scenarios. Within all platforms, FPGA is able to deliver both software and hardware solutions with low power, high performance, reconfigurability, reliability, and adaptivity characteristics, serving as the promising computing substrate for robotic applications. This paper highlights the current progress, design techniques, challenges, and open research challenges in the domain of robotic computing on FPGAs., Comment: 2022 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), June 13-15, 2022, Incheon, Korea

Theories on the origins of life propose that early cell membranes were synthesized from amphiphilic molecules simpler than phospholipids such as fatty alcohols. The discovery in the interstellar medium (ISM) of ethanolamine, the simplest phospholipid head group, raises the question whether simple amphiphilic molecules are also synthesized in space. We investigate whether precursors of fatty alcohols are present in the ISM. For this, we have carried out a spectral survey at 7, 3, 2 and 1 mm toward the Giant Molecular Cloud G+0.693-0.027 located in the Galactic Center using the IRAM 30m and Yebes 40m telescopes. Here, we report the detection in the ISM of the primary alcohol n-propanol (in both conformers Ga-n-C3H7OH and Aa-n-C3H7OH), a precursor of fatty alcohols. The derived column densities of n-propanol are (5.5+-0.4)x10^13 cm^-2 for the Ga conformer and (3.4+-0.3)x10^13 cm^-2 for the Aa conformer, which imply molecular abundances of (4.1+-0.3)x10^-10 for Ga-n-C3H7OH and of (2.5+-0.2)x10^-10 for Aa-n-C3H7OH. We also searched for the AGa conformer of n-butanol (AGa-n-C4H9OH) without success yielding an upper limit to its abundance of <4.1x10^-11. The inferred CH3OH:C2H5OH:C3H7OH:C4H9OH abundance ratios go as 1:0.04:0.006:<0.0004 toward G+0.693-0.027, i.e. they decrease roughly by one order of magnitude for increasing complexity. We also report the detection of both syn and anti conformers of vinyl alcohol, with column densities of (1.11+-0.08)x10^14 cm^-2 and (1.3+-0.4)x10^13 cm^-2, and abundances of (8.2+-0.6)x10^-10 and (9.6+-3.0)x10^-11, respectively. The detection of n-propanol, together with the recent discovery of ethanolamine in the ISM, opens the possibility that precursors of lipids according to theories of the origin of life, could have been brought to Earth from outer space., Comment: 15 pages, 10 figures, accepted for A&A

We are facing a global healthcare crisis today as the healthcare cost is ever climbing, but with the aging population, government fiscal revenue is ever dropping. To create a more efficient and effective healthcare system, three technical challenges immediately present themselves: healthcare access, healthcare equity, and healthcare efficiency. An autonomous mobile clinic solves the healthcare access problem by bringing healthcare services to the patient by the order of the patient's fingertips. Nevertheless, to enable a universal autonomous mobile clinic network, a three-stage technical roadmap needs to be achieved: In stage one, we focus on solving the inequity challenge in the existing healthcare system by combining autonomous mobility and telemedicine. In stage two, we develop an AI doctor for primary care, which we foster from infancy to adulthood with clean healthcare data. With the AI doctor, we can solve the inefficiency problem. In stage three, after we have proven that the autonomous mobile clinic network can truly solve the target clinical use cases, we shall open up the platform for all medical verticals, thus enabling universal healthcare through this whole new system., Comment: 5 pages, 1 figure

We present the first detection of ($Z$)-1,2-ethenediol, (CHOH)$_2$, the enol form of glycolaldehyde, in the interstellar medium towards the G+0.693-0.027 molecular cloud located in the Galactic Center. We have derived a column density of (1.8$\pm$0.1)$\times$10$^{13}$ cm$^{-2}$, which translates into a molecular abundance with respect to molecular hydrogen of 1.3$\times$10$^{-10}$. The abundance ratio between glycolaldehyde and ($Z$)-1,2-ethenediol is $\sim$5.2. We discuss several viable formation routes through chemical reactions from precursors such as HCO, H$_2$CO, CHOH or CH$_2$CHOH. We also propose that this species might be an important precursor in the formation of glyceraldehyde (HOCH$_2$CHOHCHO) in the interstellar medium through combination with the hydroxymethylene (CHOH) radical., Comment: Accepted for publication in The Astrophysical Journal Letters

We report the first detection of the phosphorus monoxide ion (PO$^{+}$) in the interstellar medium. Our unbiased and very sensitive spectral survey towards the G+0.693$-$0.027 molecular cloud covers four different rotational transitions of this molecule, two of which ($J$=1$-$0 and $J$=2$-$1) appear free of contamination from other species. The fit performed, assuming Local Thermodynamic Equilibrium conditions, yields a column density of $N$=(6.0$\pm$0.7)$\times$10$^{11}$ cm$^{-2}$. The resulting molecular abundance with respect to molecular hydrogen is 4.5$\times$10$^{-12}$. The column density of PO$^{+}$ normalised by the cosmic abundance of P is larger than those of NO$^{+}$ and SO$^{+}$, normalised by N and S, by factors of 3.6 and 2.3, respectively. The $N$(PO$^{+}$)/$N$(PO) ratio is 0.12$\pm$0.03, more than one order of magnitude higher than those of $N$(SO$^{+}$)/$N$(SO) and $N$(NO$^{+}$)/$N$(NO). These results indicate that P is more efficiently ionised in the ISM than N and S. We have performed new chemical models that confirm that the PO$^+$ abundance is strongly enhanced in shocked regions with high values of cosmic-ray ionisation rates (10$^{-15}-$10$^{-14}$ s$^{-1}$), as occurs in the G+0.693$-$0.027 molecular cloud. The shocks sputter the interstellar icy grain mantles, releasing into the gas phase most of their P content, mainly in the form of PH$_3$, which is converted into atomic P, and then ionised efficiently by cosmic rays, forming P$^+$. Further reactions with O$_2$ and OH produce PO$^{+}$. The cosmic-ray ionisation of PO might also contribute significantly, which would explain the high $N$(PO$^{+}$)/$N$(PO) observed. The relatively high gas-phase abundance of PO$^{+}$ with respect to other P-bearing species stresses the relevance of this species in the interstellar chemistry of P., Comment: Accepted in Frontiers in Astronomy and Space Sciences

Simultaneous Localization and Mapping (SLAM) estimates agents' trajectories and constructs maps, and localization is a fundamental kernel in autonomous machines at all computing scales, from drones, AR, VR to self-driving cars. In this work, we present an energy-efficient and runtime-reconfigurable FPGA-based accelerator for robotic localization. We exploit SLAM-specific data locality, sparsity, reuse, and parallelism, and achieve >5x performance improvement over the state-of-the-art. Especially, our design is reconfigurable at runtime according to the environment to save power while sustaining accuracy and performance., Comment: First three authors contributed equally. 2 pages, 6 figures, IEEE Custom Integrated Circuits Conference (CICC), April 24-27, 2022, Newport Beach, CA, USA