Search

High-redshift radio(-loud) galaxies (H$z$RGs) are massive galaxies with powerful radio-loud active galactic nuclei (AGNs) and serve as beacons for protocluster identification. However, the interplay between H$z$RGs and the large-scale environment remains unclear. To understand the connection between H$z$RGs and the surrounding obscured star formation, we investigated the overdensity and spatial distribution of submillimeter-bright galaxies (SMGs) in the field of 4C\,23.56, a well-known H$z$RG at $z=2.48$. We used SCUBA-2 data ($\sigma\,{\sim}\,0.6$\,mJy) to estimate the $850\,{\rm \mu m}$ source number counts and examine the radial and azimuthal overdensities of the $850\,{\rm \mu m}$ sources in the vicinity of the H$z$RG. The angular distribution of SMGs is inhomogeneous around the H$z$RG 4C\,23.56, with fewer sources oriented along the radio jet. We also find a significant overdensity of bright SMGs (${\rm S}_{850\rm\,\mu m}\geq5\,$mJy). Faint and bright SMGs exhibit different spatial distributions. The former are concentrated in the core region, while the latter prefer the outskirts of the H$z$RG field. High-resolution observations show that the seven brightest SMGs in our sample are intrinsically bright, suggesting that the overdensity of bright SMGs is less likely due to the source multiplicity.

Huan-Huan Shen,1,2,* Jie-Fei Peng,1,3,* Ran-Ran Wang,4,* Ping-Yu Wang,1,5 Jia-Xiang Zhang,1 Hong-Fang Sun,1 Yan Liang,1 Yan-Mei Li,6 Jiang-Nan Xue,7 You-Jie Li,1 Guang-Bin Sun,1,* Shu-Yang Xie1,2,* 1Department of Biochemistry and Molecular Biology, Binzhou Medical University, YanTai, Shandong, 264003, People’s Republic of China; 2Shandong Laboratory of Advanced Materials and Green Manufacturing, Yantai, Shandong, 264000, People’s Republic of China; 3Department of Clinical Laboratory, the Affiliated Taian City Central Hospital of Qingdao University, Taian, 271000, People’s Republic of China; 4Institute of Rehabilitation Medicine, School of Rehabilitation Medicine, Binzhou Medical University, Yantai, Shandong, 264003, People’s Republic of China; 5Department of Epidemiology, Binzhou Medical University, YanTai, ShanDong, 264003, People’s Republic of China; 6Department of Immune Rheumatism, Yantaishan Hospital, Yantai, Shandong, 264000, People’s Republic of China; 7Department of Immunology, Binzhou Medical University, Yantai, Shandong, 264003, People’s Republic of China*These authors contributed equally to this workCorrespondence: Shu-Yang Xie; Guang-Bin Sun, Department of Biochemistry and Molecular Biology, Binzhou Medical University, YanTai, Shandong, 264003, People’s Republic of China, Tel +86 535 6913010 ; +86 535 6913335, Fax +86 535 6913163, Email xieshuyang@bzmc.edu.cn; bingo@bzmc.edu.cnPurpose: The drug resistance and low response rates of immunotherapy limit its application. This study aimed to construct a new nanoparticle (CaCO3-polydopamine-polyethylenimine, CPP) to effectively deliver interleukin-12 (IL-12) and suppress cancer progress through immunotherapy.Methods: The size distribution of CPP and its zeta potential were measured using a Malvern Zetasizer Nano-ZS90. The morphology and electrophoresis tentative delay of CPP were analyzed using a JEM-1400 transmission electron microscope and an ul

We present a statistical study of the properties of diffuse HI in ten nearby galaxies, comparing the HI detected by the single-dish telescope FAST (FEASTS program) and the interferometer VLA (THINGS program), respectively. The THINGS' observation missed HI with a median of 23% due to the short-spacing problem of interferometry and limited sensitivity. We extract the diffuse HI by subtracting the dense HI, which is obtained from the THINGS data with a uniform flux-density threshold, from the total HI detected by FAST. Among the sample, the median diffuse-HI fraction is 34%, and more diffuse HI is found in galaxies exhibiting more prominent tidal-interaction signatures. The diffuse HI we detected seems to be distributed in disk-like layers within a typical thickness of $1\,\text{kpc}$, different from the more halo-like diffuse HI detected around NGC 4631 in a previous study. Most of the diffuse HI is cospatial with the dense HI and has a typical column density of $10^{17.7}$-$10^{20.1}\,\text{cm}^{-2}$. The diffuse and dense HI exhibits a similar rotational motion, but the former lags by a median of 25% in at least the inner disks, and its velocity dispersions are typically twice as high. Based on a simplified estimation of circum-galactic medium properties and assuming pressure equilibrium, the volume density of diffuse HI appears to be constant within each individual galaxy, implying its role as a cooling interface. Comparing with existing models, these results are consistent with a possible link between tidal interactions, the formation of diffuse HI, and gas accretion., Comment: 45 pages, 23 figures. In press at ApJ. Data will be released at the FEASTS site upon publication

We present observations using the NOrthern Extended Millimetre Array (NOEMA) of CO and $\rm H_{2}O$ emission lines, and the underlying dust continuum in two quasars at $z \sim 6$, i.e., P215-16 at $z$ = 5.78 and J1429+5447 at $z$ = 6.18. Notably, among all published CO SLEDs of quasars at $z \sim 6$, the two systems reveal the highest and the lowest CO level of excitation, respectively. Our radiative transfer modeling of the CO SLED of P215-16 suggests that the molecular gas heated by AGN could be a plausible origin for the high CO excitation. For J1429+5447, we obtain the first well-sampled CO SLED (from transitions from 2-1 to 10-9) of a radio-loud quasar at $z\gtrsim 6$. Analysis of the CO SLED suggests that a single photo-dissociation region (PDR) component could explain the CO excitation in the radio-loud quasar J1429+5447. This work highlights the utility of the CO SLED in uncovering the ISM properties in these young quasar-starburst systems at the highest redshift. The diversity of the CO SLEDs reveals the complexities in gas conditions and excitation mechanisms at their early evolutionary stage., Comment: Accepted for publication in Apj

Qianqian Li,* Ran Wang,* Xingshun Qi Department of Gastroenterology, General Hospital of Northern Theater Command, Shenyang, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xingshun Qi, Department of Gastroenterology, General Hospital of Northern Theater Command, No. 83 Wenhua Road, Shenyang, Liaoning Province, 110840, People’s Republic of China, Tel +86-24-28897603, Fax +86-24-28851113, Email xingshunqi@126.comAbstract: Isolated splenic vein thrombosis (ISVT) is a very rare venous thromboembolism in the absence of pancreatic diseases, which can cause acute abdominal pain and chronic left-side portal hypertension. Herein, we reported a 40-year-old female patient who developed ISVT after taking oral contraceptives. Anticoagulation with oral rivaroxaban was the first-line choice of therapy in this case. Since then, abdominal pain alleviated, but she did not achieve vessel recanalization. Thus, a 7-day systemic thrombolysis with urokinase was given. Abdominal pain disappeared, but ISVT was not significantly improved. During follow-up period, long-term anticoagulation with oral rivaroxaban was given. Collectively, this case indicates the possibility of oral contraceptives as a risk factor of ISVT as well as anticoagulation combined with systemic thrombolysis as a choice of treatment for ISVT. Certainly, long-term follow-up is necessary in this case.Keywords: splenic vein thrombosis, oral contraceptives, anticoagulation, rivaroxaban, thrombolysis

This work introduces a novel value decomposition algorithm, termed \textit{Dynamic Deep Factor Graphs} (DDFG). Unlike traditional coordination graphs, DDFG leverages factor graphs to articulate the decomposition of value functions, offering enhanced flexibility and adaptability to complex value function structures. Central to DDFG is a graph structure generation policy that innovatively generates factor graph structures on-the-fly, effectively addressing the dynamic collaboration requirements among agents. DDFG strikes an optimal balance between the computational overhead associated with aggregating value functions and the performance degradation inherent in their complete decomposition. Through the application of the max-sum algorithm, DDFG efficiently identifies optimal policies. We empirically validate DDFG's efficacy in complex scenarios, including higher-order predator-prey tasks and the StarCraft II Multi-agent Challenge (SMAC), thus underscoring its capability to surmount the limitations faced by existing value decomposition algorithms. DDFG emerges as a robust solution for MARL challenges that demand nuanced understanding and facilitation of dynamic agent collaboration. The implementation of DDFG is made publicly accessible, with the source code available at \url{https://github.com/SICC-Group/DDFG}., Comment: submitted to Nature Communications

Semi-supervised symmetric non-negative matrix factorization (SNMF) utilizes the available supervisory information (usually in the form of pairwise constraints) to improve the clustering ability of SNMF. The previous methods introduce the pairwise constraints from the local perspective, i.e., they either directly refine the similarity matrix element-wisely or restrain the distance of the decomposed vectors in pairs according to the pairwise constraints, which overlook the global perspective, i.e., in the ideal case, the pairwise constraint matrix and the ideal similarity matrix possess the same low-rank structure. To this end, we first propose a novel semi-supervised SNMF model by seeking low-rank representation for the tensor synthesized by the pairwise constraint matrix and a similarity matrix obtained by the product of the embedding matrix and its transpose, which could strengthen those two matrices simultaneously from a global perspective. We then propose an enhanced SNMF model, making the embedding matrix tailored to the above tensor low-rank representation. We finally refine the similarity matrix by the strengthened pairwise constraints. We repeat the above steps to continuously boost the similarity matrix and pairwise constraint matrix, leading to a high-quality embedding matrix. Extensive experiments substantiate the superiority of our method. The code is available at https://github.com/JinaLeejnl/TSNMF.

Shiyun Lv,1,* Lijun Sun,1,* Tongzeng Li,1,* Ruojing Bai,1 Man Dai,2,3 Ran Wang,1 Yuanyi Zhai,1 Wei Hua,1 Aixin Li,1 Ruolei Xin,2 Lili Dai1 1Beijing Youan Hospital, Capital Medical University, Beijing, People’s Republic of China; 2Institute for STD/AIDS Prevention and Treatment, Beijing Center for Disease Prevention and Control, Beijing, People’s Republic of China; 3School of Public Health, Chinese Medical University, Shenyang, People’s Republic of China*These authors contributed equally to this workCorrespondence: Lili Dai, Beijing Youan Hospital, Capital Medical University, Beijing, 100069, People’s Republic of China, Tel +86 10 83911069, Email lilydaier@ccmu.edu.cn Ruolei Xin, Institute for STD/AIDS Prevention and Treatment, Beijing Center for Disease Prevention and Control, Beijing, 100013, People’s Republic of China, Tel +86 10 64407364, Email xinruolei@sina.comObjective: To analyze the antiretroviral resistance in people living with HIV (PLWH) who developed low-level viremia (LLV) during antiretroviral therapy (ART) via sequencing of their HIV-1 proviral DNA and RNA and comparisons of their proviral DNA genotyping data with their past and synchronous RNA genotyping data.Patients and Methods: PLWH with LLV while receiving ART for 6 months or longer from January 2020 to September 2021 were included. HIV-1 proviral DNA and RNA were extracted from white-blood cells and concentrated plasma by ultracentrifugation, respectively, and HIV-1 pol gene fragments were amplified and sequenced. The concordance in the detection of resistance-associated mutations (RAMs) were examined between proviral DNA vs past RNA genotyping and proviral DNA vs synchronous RNA genotyping.Results: Of the 150 PLWH with LLV, 117 proviral DNA pol sequences detected in 105 PLWH were successfully amplified and RAMs were present in 27.6% and the rate of RAMs conferring low-level or greater resistance to antiretrovirals examined was 17.1%. Fifty-six and 5

The defense of Use-After-Free (UAF) exploits generally could be guaranteed via static or dynamic analysis, however, both of which are restricted to intrinsic deficiency. The static analysis has limitations in loop handling, optimization of memory representation and constructing a satisfactory test input to cover all execution paths. While the lack of maintenance of pointer information in dynamic analysis may lead to defects that cannot accurately identify the relationship between pointers and memory. In order to successfully exploit a UAF vulnerability, attackers need to reference freed memory. However, main existing schemes barely defend all types of UAF exploits because of the incomplete check of pointers. To solve this problem, we propose UAF-GUARD to defend against the UAF exploits via fine-grained memory permission management. Specially, we design two key data structures to enable the fine-grained memory permission management to support efficient relationship search for pointers and memory, which is the key design of our defending scheme against UAF exploits. In addition, UAF-GUARD can precisely locate the position of UAF vulnerabilities, so that malicious programs can be terminated in the place where the abnormality is discovered. We implement UAF-GUARD on a 64-bit Linux system, and further use UAF-GUARD to transform a program into a suitable version that can defend against UAF vulnerabilities exploits. Compared with main existing schemes UAF-GUARD is able to effectively and efficiently defend against all the three types of UAF exploits with acceptable space overhead (26.4% for small programs and 0.3% for large programs) and time complexity (21.9%).

The construction industry's commitment to achieving carbon neutrality has underscored the urgency of promoting green and low-carbon sustainable affordable housing. However, the development process has encountered several challenges, including conflicts between the central and local governments arising from differences in value preferences, financial constraints faced by local governments, inadequate access mechanisms, lenient screening processes, insufficient funding, and remote locations. Despite its significance, the policies related to affordable housing, especially in the context of assembly affordable housing, have received limited systematic examination. To address this research gap, this paper presents a comprehensive review and analysis of China's affordable housing policies. Firstly, it compiles and compares recent affordable housing policies in China, serving as a valuable reference for future affordable housing construction endeavors. Secondly, it conducts an in-depth analysis of the barriers and challenges obstructing affordable housing development in China, and proposing corresponding measures for improvement. Moreover, this paper identifies significant opportunities for affordable housing development in the country and explores the potential synergy between the development of assembly buildings and affordable housing by leveraging their respective attributes. By illuminating pertinent policies and associated issues, this research aims to inform policymakers, practitioners, and stakeholders involved in the affordable housing sector. Additionally, it aims to stimulate further research and innovation in the field, contributing to effective and sustainable housing solutions for low-income communities and society at large. This paper systematically analyzes the current status of affordable housing policies, challenges and opportunities. It also discusses the application of assembly building techniques in the realm of affordable housing, proving valuable, Design & Construction Management, Real Estate Management

Elimination of specific enteropathogenic microorganisms is critical to gut health. However, the complexity of the gut community makes it challenging to target specific bacterial organisms. Accumulating evidence suggests that various foods can change the abundance of intestinal bacteria by modulating prophage induction. By using pathogenic Escherichia coli (E. coli) ATCC 25922 as a model in this research, we explored the potential of dietary modulation of prophage induction and subsequent bacterial survival. Among a panel of sugars tested in vitro, D-xylose was shown to efficiently induce prophages in E. coli ATCC 25922, which depends, in part, upon the production of D-lactic acid. In an enteric mouse model, prophage induction was found to be further enhanced in response to propionic acid. Dietary D-xylose increased the proportion of Clostridia which converted D-lactic acid to propionic acid. Intestinal propionic acid levels were diminished, following either oral gavage with the dehydrogenase gene (ldhA)-deficient E. coli ATCC 25922 or depletion of intestinal Clostridia by administration of streptomycin. D-Xylose metabolism and exposure to propionic acid triggered E. coli ATCC 25922 SOS response that promoted prophage induction. E. coli ATCC 25922 mutant of RecA, a key component of SOS system, exhibited decreased phage production. These findings suggest the potential of using dietary components that can induce prophages as antimicrobial alternatives for disease control and prevention by targeted elimination of harmful gut bacteria.

In women, ovarian cancer is a common gynecological cancer associated with poor prognosis, reoccurrence and chemoresistance. Scoulerine, a benzylisoquinoline alkaloid, has been reported effective against several carcinomas. Thus, we investigated the impact of scoulerine on ovarian cancer cells (OVCAR3). Cell viability was assessed by MTT assay, migration was determined by Boyden Chamber assay, while the invasion was monitored by Boyden Chamber assay using the matrigel. The stemness properties of OVCAR3 cells were observed by tumorsphere assay. Epithelial to mesenchymal transition (EMT) and stemness-related protein markers were monitored by real-time PCR analysis and immunoblotting. Scoulerine inhibits the viability of OVCAR3 cells with the IC50 observed at 10 µmol L–1 after 48 h treatment. Scoulerine inhibited the colony-forming ability, migration and invasiveness of OVCAR3 cells in a dose-dependent fashion. Scoulerine treatment also drastically reduced the spheroid-forming ability of OVCAR3 cells. The mesenchymal and stemness-related markers like N-cadherin, vimentin, CD-44, Oct-4, Sox-2 and Aldh1A1 were downregulated, whereas the epithelial markers like E-cadherin and CD-24 were upregulated in scoulerine-treated cells. The upstream PI3K/Akt/mTOR-axis was downregulated in scoulerine-treated cells. We concluded that scoulerine successfully perturbs the cancerous properties of OVCAR3 cells by targeting the PI3K/Akt/mTOR axis. In vivo studies revealed a substantial decrease in tumor mass and volume after scoulerine treatment. Furthermore, scoulerine treatment was found to decrease oxidative stress factors in ovarian cancer mice model. Scoulerine is a potential anticancer agent against ovarian cancer and can be considered as a lead molecule for this malignancy, provided further investigations are performed.

We report the first statistical analyses of [CII] and dust continuum observations in six strong OI absorber fields at the end of the reionization epoch obtained by the Atacama Large Millimeter/Submillimeter Array (ALMA). Combined with one [CII] emitter reported in Wu et al. (2021), we detect one OI-associated [CII] emitter in six fields. At redshifts of OI-absorbers in non-detection fields, no emitters are brighter than our detection limit within impact parameters of 50 kpc and velocity offsets between $\pm200\ {\rm km\ s^{-1}}$. The averaged [CII]-detection upper limit is $< 0.06$ Jy ${\rm km\ s^{-1}}$ (3$\sigma$), corresponding to the [CII] luminosity of $L_{\rm [CII]} <5.8\times 10^7\ L_{\odot}$ and the [CII]-based star formation rate of ${\rm SFR_{\rm [CII]}} < 5.5$ $M_\odot$ yr$^{-1}$. Cosmological simulations suggest that only $\sim10^{-2.5}$ [CII] emitters around [OI] absorbers have comparable SFR to our detection limit. Although the detection in one out of six fields is reported, an order of magnitude number excess of emitters obtained from our ALMA observations supports that the contribution of massive galaxies that caused the metal enrichment cannot be ignored. Further, we also found 14 tentative galaxy candidates with S/N of $\approx4.3$ at large impact parameters ($>50$ kpc) and having larger outflow velocities within $\pm 600$ km s$^{-1}$. If these detections are confirmed in the future, then the mechanism of pushing metals at larger distances with higher velocities needs to be further explored from the theoretical side., Comment: Accepted for publication in ApJ. Main text 10 pages, 5 figures

Organic dyes in the excited singlet state (S-1) decay via intersystem crossing (ISC) to the triplet state, radiative dissipation as fluorescence, or nonradiative decay for thermal deactivation. Although many studies are conducted to improve ISC and fluorescence efficiency, few have optimized S-1 decay via thermal deactivation, which is crucial for designing photothermal agents. A strategy for inhibiting radiative decay and ISC by introducing electron withdraw groups (EWGs) into the meso position of heptamethine cyanines (Cy7) is reported here, which allows S-1 energy decay via nonradiative relaxation. The decrease in the electron density of Cy7 caused by EWGs improved the photostability, which is important for biological applications because conventional cyanine dyes are easily photobleached. The EWG substitutes acted as efficient rotation groups with low-energy barriers, narrowing the energy gap between S-1 and the ground state and considerably improving the photothermal conversion efficiency (PCE). The PCE of CF(3)cy with the strongest EWG is increased up to 83%. Liposome is used as a carrier to improve the biocompatibility and tumor retention of CF(3)cy, which is combined with the toll-like receptor agonist resiquimod (R848) for synergistic photothermal immunotherapy against both primary and distant tumors and elicits a long-lasting immunological memory effect.

Accretion of black holes at near-Eddington or super-Eddington rates is the most powerful episode that drives black hole growth, and it may work in several types of objects. However, the physics of accretion and jet-disc coupling in such a state remains unclear, mainly because the associated jets are not easily detectable due to the extremely weak emission or possibly episodic nature of the jets. Only a few near/super-Eddington systems have demonstrated radio activity, and it remains unclear whether there is a jet and what are their properties, in super-Eddington active galactic nuclei (AGNs) (and ultraluminous X-ray sources). The deficit is mainly due to the complex radio mixing between the origins of jets and others, such as star formation activity, photo-ionized gas, accretion disk wind, and coronal activity. In this work, we conducted high-resolution very long baseline interferometry (VLBI) observations to explore the jets in the highly accreting narrow-line Seyfert I system IZw1. Our observations successfully revealed small-scale jets (with a linear size of $\sim45$ parsec) at both 1.5 and 5 GHz, based on the high radio brightness temperature, radio morphology, and spectral index distribution. Interestingly, the lack of a flat-spectrum radio core and knotty jet structures imply episodic ejections in IZw1, which resemble the ejection process in Galactic X-ray binaries that are in the canonical very high state. The high accretion rates and jet properties in the AGN IZw1 may support the AGN/XRB analogy in the extreme state., Comment: 19 pages, 8 figures and 4 tables, submitted to ApJ. 2nd round referee report received. comments welcome

Stars form in galaxies, from gas that has been accreted from the intergalactic medium. Simulations have shown that recycling of gas-the reaccretion of gas that was previously ejected from a galaxy-could sustain star formation in the early Universe. We observe the gas surrounding a massive galaxy at redshift 2.3 and detect emission lines from neutral hydrogen, helium, and ionized carbon that extend 100 kiloparsecs from the galaxy. The kinematics of this circumgalactic gas is consistent with an inspiraling stream. The carbon abundance indicates that the gas had already been enriched with elements heavier than helium, previously ejected from a galaxy. We interpret the results as evidence of gas recycling during high-redshift galaxy assembly., Comment: Published in Science, 5 May 2023 (accepted version), Main text 20 pages, four figures in the main text, and 13 figures and 4 tables in the supplementary materials

The formation of the first supermassive black holes is expected to have occurred in some most pronounced matter and galaxy overdensities in the early universe. We have conducted a sub-mm wavelength continuum survey of 54 $z\sim6$ quasars using the Submillimeter Common-User Bolometre Array-2 (SCUBA2) on the James Clerk Maxwell Telescope (JCMT) to study the environments around $z \sim 6$ quasars. We identified 170 submillimeter galaxies (SMGs) with above 3.5$\sigma$ detections at 450 or 850 \um\, maps. Their FIR luminosities are 2.2 - 6.4 $\times$ 10$^{12} L_{\odot}$, and star formation rates are $\sim$ 400 - 1200 M$_{\odot}$ yr$^{-1}$. We also calculated the SMGs differential and cumulative number counts in a combined area of $\sim$ 620 arcmin$^2$. To a $4\sigma$ detection (at $\sim$ 5.5 mJy), SMGs overdensity is $0.68^{+0.21}_{-0.19}$($\pm0.19$), exceeding the blank field source counts by a factor of 1.68. We find that 13/54 quasars show overdensities (at $\sim$ 5.5 mJy) of $\delta_{SMG}\sim$ 1.5 - 5.4. The combined area of these 13 quasars exceeds the blank field counts with the overdensity to 5.5 mJy of \dsmg $\sim$ $2.46^{+0.64}_{-0.55}$($\pm0.25$) in the regions of $\sim$ 150 arcmin$^2$. However, the excess is insignificant on the bright end (e.g., 7.5 mJy). We also compare results with previous environmental studies of Lyman alpha emitters (LAEs) and Lyman-Break Galaxies (LBGs) on a similar scale. Our survey presents the first systematic study of the environment of quasars at $z\sim6$. The newly discovered SMGs provide essential candidates for follow-up spectroscopic observations to test whether they reside in the same large-scale structures as the quasars and search for protoclusters at an early epoch., Comment: 12 pages, 8 figures and 2 tables, accepted for publication in ApJ

We present new NOrthern Extended Millimeter Array (NOEMA) observations of the CO(2--1) emission in eight of the brightest Palomar-Green quasars at $z \lesssim 0.5$ to investigate the role of active galactic nuclei (AGN) feedback in luminous quasars detected at low redshifts. We detect CO(2--1) emission in three objects, from which we derive CO luminosities, molecular gas masses and fractions, and gas depletion times. In combination with data available in the literature, we build a total sample of 138 local type 1 AGNs with CO(2--1) measurements. We compare the AGN properties with the host galaxy molecular gas properties, considering the systems non-detected in CO emission. We find that the CO luminosity does not correlate with AGN luminosity and Eddington ratio, while the molecular gas fraction is weakly correlated with Eddington ratio. The type 1 AGNs can be roughly separated into two populations in terms of infrared-to-CO luminosity ratio, one population presenting values typically found in normal star-forming systems, while the other have lower ratio values, comparable to those measured for starbursts. We find no evidence that AGN feedback rapidly quenches star formation in type 1 AGNs. Our results may imply an underlying the role of host galaxy gravitational instabilities or the fast inflow of cold gas in triggering AGN activity., Comment: 20 pages, 9 figures, 4 tables. Accepted for publication in ApJ

We present a study of the molecular gas distribution and kinematics in the cicumnuclear region (radii $\lesssim 2\,$kpc) of the $z\approx0.061$ quasar I$\,$Zwicky$\,$1 using a collection of available Atacama Large Millimeter/submillimeter Array (ALMA) observations of the carbon monoxide (CO) emission. With an angular resolution of $\sim0.36''$ (corresponding to $\sim\,400\,\rm pc$), the host galaxy sub-structures including the nuclear molecular gas disk, spiral arms, and a compact bar-like component are resolved. We analyzed the gas kinematics based on the CO image cube and obtained the rotation curve and radial distribution of velocity dispersion. The velocity dispersion is about $30\,\rm km\,s^{-1}$ in the outer CO disk region and rises up to $\gtrsim 100\,\rm km\,s^{-1}$ at radius $\lesssim 1\,$kpc, suggesting that the central region of disk is dynamically hot. We constrain the CO-to-$\rm H_2$ conversion factor, $\alpha_{\rm CO}$, by modeling the cold gas disk dynamics. We find that, with prior knowledge about the stellar and dark matter components, the $\alpha_{\rm CO}$ value in the circumnuclear region of this quasar host galaxy is $1.55_{-0.49}^{+0.47}\,M_\odot\,\left(\rm K\,km\,s^{-1}\,pc^2\right)^{-1}$, which is between the value reported in ultra-luminous infrared galaxies and in the Milky-Way. The central 1$\,$kpc region of this quasar host galaxy has significant star formation activity, which can be identified as a nuclear starburst. We further investigate the high velocity dispersion in the central region. We find that the ISM turbulent pressure derived from the gas velocity dispersion is in equilibrium with the weight of the ISM. This argues against extra power from AGN feedback that significantly affects the kinematics of the cold molecular gas., Comment: 20 pages, 10 figures. Accepted for publication in ApJ

Characterizing the physical conditions (density, temperature, ionization state, metallicity, etc) of the interstellar medium is critical to our understanding of the formation and evolution of galaxies. Here we present a multi-line study of the interstellar medium in the host galaxy of a quasar at z~6.4, i.e., when the universe was 840 Myr old. This galaxy is one of the most active and massive objects emerging from the dark ages, and therefore represents a benchmark for models of the early formation of massive galaxies. We used the Atacama Large Millimeter Array to target an ensemble of tracers of ionized, neutral, and molecular gas, namely the fine-structure lines: [OIII] 88$\mu$m, [NII] 122$\mu$m, [CII] 158$\mu$m, and [CI] 370$\mu$m and the rotational transitions of CO(7-6), CO(15-14), CO(16-15), and CO(19-18); OH 163.1$\mu$m and 163.4$\mu$m; and H$_2$O 3(0,3)-2(1,2), 3(3,1)-4(0,4), 3(3,1)-3(2,2), 4(0,4)-3(1,3), 4(3,2)-4(2,3). All the targeted fine-structure lines are detected, as are half of the targeted molecular transitions. By combining the associated line luminosities, the constraints on the dust temperature from the underlying continuum emission, and predictions from photoionization models of the interstellar medium, we find that the ionized phase accounts for about one third of the total gaseous mass budget, and is responsible for half of the total [CII] emission. It is characterized by high density (n~180 cm$^{-3}$), typical of HII regions. The spectral energy distribution of the photoionizing radiation is comparable to that emitted by B-type stars. Star formation also appears to drive the excitation of the molecular medium. We find marginal evidence for outflow-related shocks in the dense molecular phase, but not in other gas phases. This study showcases the power of multi-line investigations in unveiling the properties of the star-forming medium in galaxies at cosmic dawn., Comment: 16 pages, 14 figures. Accepted for publication in A&A

Kiwifruit (Actinidia spp) is a woody, perennial and deciduous vine. In this genus, there are multiple ploidy levels but the main cultivated cultivars are polyploid. Despite the availability of many genomic resources in kiwifruit, SNP genotyping is still a challenge given these different levels of polyploidy. Recent advances in SNP array technologies have offered a high-throughput genotyping platform for genome-wide DNA polymorphisms. In this study, we developed a high-density SNP genotyping array to facilitate genetic studies and breeding applications in kiwifruit. SNP discovery was performed by genome-wide DNA sequencing of 40 kiwifruit genotypes. The identified SNPs were stringently filtered for sequence quality, predicted conversion performance and distribution over the available Actinidia chinensis genome. A total of 134 729 unique SNPs were put on the array. The array was evaluated by genotyping 400 kiwifruit individuals. We performed a multidimensional scaling analysis to assess the diversity of kiwifruit germplasm, showing that the array was effective to distinguish kiwifruit accessions. Using a tetraploid F1 population, we constructed an integrated linkage map covering 3060.9 cM across 29 linkage groups and performed QTL analysis for the sex locus that has been identified on Linkage Group 3 (LG3) in Actinidia arguta. Finally, our dataset presented evidence of tetrasomic inheritance with partial preferential pairing in A. arguta. In conclusion, we developed and evaluated a 135K SNP genotyping array for kiwifruit. It has the advantage of a comprehensive design that can be an effective tool in genetic studies and breeding applications in this high-value crop.

This paper studies the learning-to-control problem under process and sensing uncertainties for dynamical systems. In our previous work, we developed a data-based generalization of the iterative linear quadratic regulator (iLQR) to design closed-loop feedback control for high-dimensional dynamical systems with partial state observation. This method required perfect simulation rollouts which are not realistic in real applications. In this work, we briefly introduce this method and explore its efficacy under process and sensing uncertainties. We prove that in the fully observed case where the system dynamics are corrupted with noise but the measurements are perfect, it still converges to the global minimum. However, in the partially observed case where both process and measurement noise exist in the system, this method converges to a biased "optimum". Thus multiple rollouts need to be averaged to retrieve the true optimum. The analysis is verified in two nonlinear robotic examples simulated in the above cases.

The Cholinergic Pathways Hyperintensities Scale (CHIPS) is a visual rating scale used to assess the extent of cholinergic white matter hyperintensities in T2-FLAIR images, serving as an indicator of dementia severity. However, the manual selection of four specific slices for rating throughout the entire brain is a time-consuming process. Our goal was to develop a deep learning-based model capable of automatically identifying the four slices relevant to CHIPS. To achieve this, we trained a 4-class slice classification model (BSCA) using the ADNI T2-FLAIR dataset (N=150) with the assistance of ResNet. Subsequently, we tested the model's performance on a local dataset (N=30). The results demonstrated the efficacy of our model, with an accuracy of 99.82% and an F1-score of 99.83%. This achievement highlights the potential impact of BSCA as an automatic screening tool, streamlining the selection of four specific T2-FLAIR slices that encompass white matter landmarks along the cholinergic pathways. Clinicians can leverage this tool to assess the risk of clinical dementia development efficiently., Comment: 8 pages, 2 figures, 2 tables

Recent advances in machine learning have made revolutionary breakthroughs in computer games, image and natural language understanding, and scientific discovery. Foundation models and large-scale language models (LLMs) have recently achieved human-like intelligence thanks to BigData. With the help of self-supervised learning (SSL) and transfer learning, these models may potentially reshape the landscapes of neuroscience research and make a significant impact on the future. Here we present a mini-review on recent advances in foundation models and generative AI models as well as their applications in neuroscience, including natural language and speech, semantic memory, brain-machine interfaces (BMIs), and data augmentation. We argue that this paradigm-shift framework will open new avenues for many neuroscience research directions and discuss the accompanying challenges and opportunities.

Large-scale pre-trained language models (LLMs) have demonstrated exceptional performance in various natural language processing (NLP) tasks. However, the massive size of these models poses huge challenges for their deployment in real-world applications. While numerous model compression techniques have been proposed, most of them are not well-suited for achieving extreme model compression when there is a significant gap in model scale. In this paper, we introduce a novel compression paradigm called Retrieval-based Knowledge Transfer (RetriKT), which effectively transfers the knowledge of LLMs to extremely small-scale models (e.g., 1%). In particular, our approach extracts knowledge from LLMs to construct a knowledge store, from which the small-scale model can retrieve relevant information and leverage it for effective inference. To improve the quality of the model, soft prompt tuning and Proximal Policy Optimization (PPO) reinforcement learning techniques are employed. Extensive experiments are conducted on low-resource tasks from SuperGLUE and GLUE benchmarks. The results demonstrate that the proposed approach significantly enhances the performance of small-scale models by leveraging the knowledge from LLMs., Comment: EMNLP 2023 Findings

In our modern, fast-paced, and interconnected world, the importance of mental well-being has grown into a matter of great urgency. However, traditional methods such as Emotional Support Conversations (ESC) face challenges in effectively addressing a diverse range of individual personalities. In response, we introduce the Social Support Conversation (S2Conv) framework. It comprises a series of support agents and the interpersonal matching mechanism, linking individuals with persona-compatible virtual supporters. Utilizing persona decomposition based on the MBTI (Myers-Briggs Type Indicator), we have created the MBTI-1024 Bank, a group that of virtual characters with distinct profiles. Through improved role-playing prompts with behavior preset and dynamic memory, we facilitate the development of the MBTI-S2Conv dataset, which contains conversations between the characters in the MBTI-1024 Bank. Building upon these foundations, we present CharacterChat, a comprehensive S2Conv system, which includes a conversational model driven by personas and memories, along with an interpersonal matching plugin model that dispatches the optimal supporters from the MBTI-1024 Bank for individuals with specific personas. Empirical results indicate the remarkable efficacy of CharacterChat in providing personalized social support and highlight the substantial advantages derived from interpersonal matching. The source code is available in \url{https://github.com/morecry/CharacterChat}., Comment: 10 pages, 6 figures, 5 tables

Due to shortage of water resources and increasing water demands, the joint operation of multireservoir systems for balancing power generation, ecological protection, and the residential water supply has become a critical issue in hydropower management. However, the numerous constraints and nonlinearity of multiple reservoirs make solving this problem time-consuming. To address this challenge, a deep reinforcement learning approach that incorporates a transformer framework is proposed. The multihead attention mechanism of the encoder effectively extracts information from reservoirs and residential areas, and the multireservoir attention network of the decoder generates suitable operational decisions. The proposed method is applied to Lake Mead and Lake Powell in the Colorado River Basin. The experimental results demonstrate that the transformer-based deep reinforcement learning approach can produce appropriate operational outcomes. Compared to a state-of-the-art method, the operation strategies produced by the proposed approach generate 10.11% more electricity, reduce the amended annual proportional flow deviation by 39.69%, and increase water supply revenue by 4.10%. Consequently, the proposed approach offers an effective method for the multiobjective operation of multihydropower reservoir systems., Comment: 11 figures, 16 pages, submitted to Journal of Hydrology

This dissertation discusses the application of machine learning techniques on the economic causal inference and forecasting.In Chapter 2, we develop a new method, the $L_1$-regularized soft decision tree, to identify the relevant features for the heterogeneous treatment effect and confounding effect under a very flexible nonlinear potential outcomes framework for causal inference. Compared to other methods, we show that our approach can identify relevant factors without the widely used assumption of additive nonlinearity. By embedding the debiased soft decision tree into the $L_1$-based variable selection framework, we show that the $L_1$-regularized soft decision tree outperforms other variable selection methods such as lasso in nonlinear settings.Chapter 3 focuses on macroeconomic forecasting literature. This chapter introduces unFEAR, an unsupervised feature extraction clustering method aimed at facilitating crisis prediction tasks. We use unsupervised representation learning and a novel autoencoder method to extract from economic data information relevant to identify time-invariant non-overlapping clusters comprising observed crisis and non-crisis episodes. Each cluster corresponds to a different economic regime characterized by an idiosyncratic crisis generating mechanism.Chapters 4 and 5 summarize the literature of economic forecasting using two attractive machine learning techniques. Chapter 4 focuses on the Bagging and Random Forests methods. We explore Bagging, Random Forest, and their variants in various aspects of theory and practice. We also discuss applications based on these methods in economic forecasting and inference. Chapter 5 discusses Boosting. Boosting can estimate the variables of interest consistently under fairly general conditions given a large set of explanatory variables. Boosting is fast and easy to implement, which makes it one of the most popular machine learning algorithms in academia and industry.

This dissertation discusses the application of machine learning techniques on the economic causal inference and forecasting.In Chapter 2, we develop a new method, the $L_1$-regularized soft decision tree, to identify the relevant features for the heterogeneous treatment effect and confounding effect under a very flexible nonlinear potential outcomes framework for causal inference. Compared to other methods, we show that our approach can identify relevant factors without the widely used assumption of additive nonlinearity. By embedding the debiased soft decision tree into the $L_1$-based variable selection framework, we show that the $L_1$-regularized soft decision tree outperforms other variable selection methods such as lasso in nonlinear settings.Chapter 3 focuses on macroeconomic forecasting literature. This chapter introduces unFEAR, an unsupervised feature extraction clustering method aimed at facilitating crisis prediction tasks. We use unsupervised representation learning and a novel autoencoder method to extract from economic data information relevant to identify time-invariant non-overlapping clusters comprising observed crisis and non-crisis episodes. Each cluster corresponds to a different economic regime characterized by an idiosyncratic crisis generating mechanism.Chapters 4 and 5 summarize the literature of economic forecasting using two attractive machine learning techniques. Chapter 4 focuses on the Bagging and Random Forests methods. We explore Bagging, Random Forest, and their variants in various aspects of theory and practice. We also discuss applications based on these methods in economic forecasting and inference. Chapter 5 discusses Boosting. Boosting can estimate the variables of interest consistently under fairly general conditions given a large set of explanatory variables. Boosting is fast and easy to implement, which makes it one of the most popular machine learning algorithms in academia and industry.

We present new results of a 12CO(J=1-0) imaging survey using the Atacama Compact Array (ACA) for 31 HI detected galaxies in the IC 1459 and NGC 4636 groups. This is the first CO imaging survey for loose galaxy groups. We obtained well-resolved CO data (~0.7-1.5 kpc) for a total of 16 galaxies in two environments. By comparing our ACA CO data with the HI and UV data, we probe the impacts of the group environment on the cold gas components (CO and HI gas) and star formation activity. We find that CO and/or HI morphologies are disturbed in our group members, some of which show highly asymmetric CO distributions (e.g., IC 5264, NGC 7421, and NGC 7418). In comparison with isolated galaxies in the xCOLD GASS sample, our group galaxies tend to have low star formation rates and low H2 gas fractions. Our findings suggest that the group environment can change the distribution of cold gas components, including the molecular gas, and star formation properties of galaxies. This is supporting evidence that pre-processing in the group-like environment can play an important role in galaxy evolution., Comment: 42 pages, 29 figures, 7 tables, submitted to ApJS

We present high spatial resolution (0.4", 2.2kpc) observations of the CO(6-5), CO(7-6) and [CI] lines and dust continuum emission from the interstellar medium in the host galaxy of the quasar J0305$-$3150 at $z=6.6$. These, together with archival [CII] data at comparable spatial resolution, enable studies of the spatial distribution and kinematics between the ISM in different phases. When comparing the radial profiles of CO, [CII] and the dust continuum, we find that the CO and dust continuum exhibit similar spatial distributions, both of which are less extended than the [CII], indicating that the CO and dust continuum are tracing the same gas component, while the [CII] is tracing a more extended one. In addition, we derive the radial profiles of the [CII]/CO, [CII]/far-infrared (FIR), CO/FIR, and dust continuum $S_{98.7 \rm GHz}/S_{258.1 \rm GHz}$ ratios. We find a decreasing $S_{98.7 \rm GHz}/S_{258.1 \rm GHz}$ ratio with radius, possibly indicating a decrease of dust optical depth with increasing radius. We also detect some of the ISM lines and continuum emission in the companion galaxies previously discovered in the field around J0305$-$3150. Through comparing the line-to-line and line-to-FIR ratios, we find no significant differences between the quasar and its companion galaxies., Comment: 12 pages, 6 figures, accepted for publication in ApJ

We present the HI distribution of galaxies from the Continuum Halos in Nearby Galaxies - an EVLA Survey (CHANG-ES). Though the observational mode was not optimized for detecting HI, we successfully produce HI cubes for 19 galaxies. The moment-0 maps from this work are available on CHANG-ES data release website, i.e., https://www.queensu.ca/changes. Our sample is dominated by star-forming, HI-rich galaxies at distances from 6.27 to 34.1 Mpc. HI interferometric images on two of these galaxies (NGC 5792 and UGC 10288) are presented here for the first time, while 12 of our remaining sample galaxies now have better HI spatial resolutions and/or sensitivities of intensity maps than those in existing publications. We characterize the average scale heights of the HI distributions for a subset of most inclined galaxies (inclination > 80 deg), and compare them to the radio continuum intensity scale heights, which have been derived in a similar way. The two types of scale heights are well correlated, with similar dependence on disk radial extension and star formation rate surface density but different dependence on mass surface density. This result indicates that the vertical distribution of the two components may be governed by similar fundamental physics but with subtle differences., Comment: 27 pages, 10 figures, accepted for publication in MNRAS

We investigate the molecular gas content of z~6 quasar host galaxies using the IRAM / Northern Extended Millimeter Array. We target the 3mm dust continuum, and the line emission from CO(6-5), CO(7-6), [CI]2-1 in 10 infra-red-luminous quasars that have been previously studied in their 1mm dust continuum and [CII] line emission. We detect CO(7-6) at various degrees of significance in all the targeted sources, thus doubling the number of such detections in z~6 quasars. The 3mm to 1mm flux density ratios are consistent with a modified black body spectrum with a dust temperature $T_{dust}$~47 K and an optical depth $\tau_{\nu}$=0.2 at the [CII] frequency. Our study provides us with four independent ways to estimate the molecular gas mass, $M_{H2}$, in the targeted quasars. This allows us to set constraints on various parameters used in the derivation of molecular gas mass estimates, such as the mass per luminosity ratios $\alpha_{CO}$ and $\alpha_{[CII]}$, the gas-to-dust ratio $\delta_{g/d}$, and the carbon abundance [C]/H2. Leveraging either on the dust, CO, [CI], or [CII] emission yields mass estimates of the entire sample in the range $M_{H2}$~$10^{10}$ to $10^{11}$ M$_{\odot}$. We compare the observed luminosities of dust, [CII], [CI], and CO(7-6) with predictions from photo-dissociation and X-ray dominated regions. We find that the former provide better model fits to our data, assuming that the bulk of the emission arises from dense ($n_H>10^4$ cm$^{-3}$) clouds with a column density $N_{H}$~$10^{23}$ cm$^{-2}$, exposed to a radiation field with intensity $G_0$~$10^3$ (in Habing units). Our analysis reiterates the presence of massive reservoirs of molecular gas fueling star formation and nuclear accretion in $z$~6 quasar host galaxies. It also highlights the power of combined 3mm and 1mm observations for quantitative studies of the dense gas content in massive galaxies at cosmic dawn., Comment: 13 pages, 7 figures. Accepted for publication in A&A

We report deep Karl G. Jansky Very Large Array (VLA) observations of the optically ultraluminous and radio-quiet quasar SDSS J010013.02 + 280225.8 (hereafter J0100+2802) at redshift $z=$6.3. We detected the radio continuum emission at 1.5 GHz, 6 GHz, and 10 GHz. This leads to a radio power-law spectral index of $\alpha = -0.52\pm0.18$ ($S \propto \nu^{\alpha}$). The radio source is unresolved in all VLA bands with an upper limit to the size of $0.2^{\prime \prime}$ (i.e., $\sim$ 1.1 kpc) at 10 GHz. We find variability in the flux density (increase by $\sim 33\%$) and the spectral index (steepened) between observations in 2016 and 2017. We also find that the VLA 1.5 GHz flux density observed in the same year is 1.5 times that detected with the Very Long Baseline Array (VLBA) in 2016 at the same frequency. This difference suggests that half of the radio emission from J0100+2802 comes from a compact core within 40 pc, and the rest comes from the surrounding few kpc area which is diffuse and resolved out in the VLBA observations. The diffuse emission is four times brighter than that would be expected if driven by star formation. We conclude that the central active galactic nucleus is the dominant power engine of the radio emission in J0100+2802., Comment: 9 pages, 3 figures. Accepted for publication in The Astrophysical Journal

We quantify galaxy overdensities around three high-redshift quasars with known [CII] 158um companions: PJ231-20 (z=6.59), PJ308-21 (z=6.24) and J0305-3150 (z=6.61). Recent SCUBA2 imaging revealed the presence of 17 submillimeter galaxies (SMG) with sky separations $0.7'< \theta < 2.4'$ from these three quasars. We present ALMA Band 6 follow-up observations of these SCUBA2-selected SMGs to confirm their nature and redshift. We also search for continuum-undetected [CII] emitters in the ALMA pointings and make use of archival MUSE observations to search for Lyman-$\alpha$ Emitters (LAE) associated with the quasars. While most of the SCUBA2-selected sources are detected with ALMA in the continuum, no [CII] line emission could be detected, indicating that they are not at the quasar redshifts. Based on the serendipitous detection of CO 7-6 and [CI] emission lines, we find that four SMGs in the field of PJ231-20 are at z~2.4, which is coincident with the redshift of a Mg II absorber in the quasar rest-frame UV spectrum. We report the discovery of 2 LAEs within <0.6 cMpc of PJ231-20 at the same redshift, indicating a LAE overdensity around this quasar. Taken together, these observations provide new constraints on the large-scale excess of Lyman-$\alpha$- and [CII]-emitting galaxies around z>6 quasars and suggest that only wide-field observations, such as MUSE, ALMA or JWST mosaics, can reveal a comprehensive picture of large-scale structure around quasars in the first billion years of the Universe., Comment: Accepted for publication in The Astrophysical Journal

Tin sulfide (SnS) has been regarded as one of the most attractive anode materials for lithium-ion batteries (LIBs) because of its high specific capacity. However, its large volume expansion (>300%) and low electronic conductivity restrict its application. In this study, Sn2+ was anchored on Ti3C2 nanosheets through electrostatic attraction, and Ti3C2@SnS@C was synthesized through a hydrothermal method. The obtained Ti3C2@SnS@C exhibits excellent rate performance and cycle performance and effectively serves as an anode material for LIBs. It has a stable capacity of 563.5 mAh/g after 420 cycles at 500 mA/g, and this value is much higher than that of commercially available anode materials. Ti3C2 can also effectively inhibit the volume expansion of SnS particles. The volume expansion of Ti3C2@SnS@C electrode is only 56.8% after 420 cycles at 500 mA/g. This finding is much better than that of pure SnS@C electrode (209.3%).

Ectomycorrhizal fungi play a key role in forests by establishing mutualistic symbioses with woody plants. Genome analyses have identified conserved symbiosis-related traits among ectomycorrhizal fungal species, but the molecular mechanisms underlying host specificity remain poorly known. We sequenced and compared the genomes of seven species of milk-cap fungi (Lactarius, Russulales) with contrasting host specificity. We also compared these genomes with those of symbiotic and saprotrophic Russulales species, aiming to identify genes involved in their ecology and host specificity. The size of Lactarius genomes is significantly larger than other Russulales species, owing to a massive accumulation of transposable elements and duplication of dispensable genes. As expected, their repertoire of genes coding for plant cell wall-degrading enzymes is restricted, but they retained a substantial set of genes involved in microbial cell wall degradation. Notably, Lactarius species showed a striking expansion of genes encoding proteases, such as secreted ectomycorrhiza-induced sedolisins. A high copy number of genes coding for small secreted LysM proteins and Lactarius-specific lectins were detected, which may be linked to host specificity. This study revealed a large diversity in the genome landscapes and gene repertoires within Russulaceae. The known host specificity of Lactarius symbionts may be related to mycorrhiza-induced species-specific genes, including secreted sedolisins.

Pulin Li,1,* Xiaojuan Chen,2,* Sijing Zhou,3,* Xingyuan Xia,1 Enze Wang,1 Rui Han,1 Daxiong Zeng,4,5 Guanghe Fei,1 Ran Wang1 1Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Anhui Medical University, Hefei, People’s Republic of China; 2Department of Infectious Diseases, Hefei Second People’s Hospital, Hefei, People’s Republic of China; 3Department of Occupational Medicine, Hefei Third Clinical College of Anhui Medical University, Hefei, People’s Republic of China; 4Department of Pulmonary and Critical Care Medicine, Suzhou Dushu Lake Hospital, Suzhou, People’s Republic of China; 5Department of Pulmonary and Critical Care Medicine, Dushu Lake Hospital Affiliated to Soochow University, Medical Center of Soochow University, Suzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Guanghe Fei; Ran Wang, Department of Respiratory and Critical Care Medicine, the First Affiliated Hospital of Anhui Medical University, Hefei, People’s Republic of China, Tel/Fax +86 -551-62922913, Email guanghefei@hotmail.com; wangran@ahmu.edu.cnIntroduction: Lung adenocarcinoma (LUAD) is the most common type of lung cancer. DEP domain-containing 1 B (DEPDC1B) is involved in the development of several cancers; however, its role in LUAD is unknown. Therefore, we aimed to determine the biological function and prognostic value of DEPDC1B in LUAD.Material and Methods: We analyzed the correlation between DEPDC1B expression and the clinical features of LUAD and lung squamous cell carcinoma (LUSC). Survival was evaluated by generating Kaplan–Meier curves, which were used to analyze the relationship between DEPDC1B expression and prognosis in LUAD and LUSC. DEPDC1B expression in tumor and normal tissues from patients with LUAD and LUSC was determined using immunohistochemistry, and its clinical significance was analyzed. Finally, the correlatio

• Ectomycorrhizal fungi play a key role in forests by establishing mutualistic symbioses with woody plants. Genome analyses have identified conserved symbiosis-related traits among ectomycorrhizal fungal species, but the molecular mechanisms underlying host-specificity remain poorly known. • We sequenced and compared the genomes of seven species of milk-cap fungi (Lactarius, Russulales) with contrasted host-specificity. We also compared these genomes with those of symbiotic and saprotrophic Russulales species aiming to identify genes involved in their ecology and host-specificity. • The size of Lactarius genomes is significantly larger than other Russulales species, owing to a massive accumulation of transposable elements and duplication of dispensable genes. As expected, their repertoire of genes coding for plant cell wall degrading enzymes is restricted, but they retained a substantial set of genes involved in microbial cell wall degradation. Notably, Lactarius species showed a striking expansion of genes encoding proteases, such as secreted ectomycorrhiza-induced sedolisins. A high copy number of genes coding for small secreted LysM proteins and Lactarius-specific lectins were detected, which may be linked to host-specificity. • This study revealed a large diversity in the genome landscapes and gene repertoires within Russulaceae. The known host-specificity of Lactarius symbionts may be related to mycorrhiza-induced species-specific genes, including secreted sedolisins.

We present Atacama Large Millimeter/submillimeter Array (ALMA) sub-kiloparsec- to kiloparsec-scale resolution observations of the [C II], CO (9-8), and OH+ (1(1)-0(1)) lines along with their dust continuum emission toward the far-infrared (FIR) luminous quasar SDSS J231038.88+185519.7 at z = 6.0031, to study the interstellar medium distribution, the gas kinematics, and the quasar-host system dynamics. We decompose the intensity maps of the [C II] and CO (9-8) lines and the dust continuum with two-dimensional elliptical Sersic models. The [C II] brightness follows a flat distribution with a Sersic index of 0.59. The CO (9-8) line and the dust continuum can be fit with an unresolved nuclear component and an extended Sersic component with a Sersic index of similar to 1, which may correspond to the emission from an active galactic nucleus dusty molecular torus and a quasar host galaxy, respectively. The different [C II] spatial distribution may be due to the effect of the high dust opacity, which increases the FIR background radiation on the [C II] line, especially in the galaxy center, significantly suppressing the [C II] emission profile. The dust temperature drops with distance from the center. The effective radius of the dust continuum is smaller than that of the line emission and the dust mass surface density, but is consistent with that of the star formation rate surface density. This may indicate that the dust emission is a less robust tracer of the dust and gas distribution but is a decent tracer of the obscured star formation activity. The OH+ (1(1)-0(1)) line shows a P-Cygni profile with an absorption at similar to-400 km s(-1), which may indicate an outflow with a neutral gas mass of (6.2 +/- 1.2)x10(8) M-? along the line of sight. We employed a three-dimensional tilted ring model to fit the [C II] and CO (9-8) data cubes. The two lines are both rotation dominated and trace identical disk geometries and gas motions. This suggest that the [C II] and CO (9-8) g

This paper considers the problem of system identification for linear time varying systems. We propose a new system realization approach that uses an "information-state" as the state vector, where the "information-state" is composed of a finite number of past inputs and outputs. The system identification algorithm uses input-output data to fit an autoregressive moving average model (ARMA) to represent the current output in terms of finite past inputs and outputs. This information-state-based approach allows us to directly realize a state-space model using the estimated time varying ARMA paramters linear time varying (LTV) systems. The paper develops the theoretical foundation for using ARMA parameters-based system representation using only the concept of linear observability, details the reasoning for exact output modeling using only the finite history, and shows that there is no need to separate the free and the forced response for identification. The paper also discusses the implications of using the information-state system for optimal output feedback control and shows that the solution obtained using a suitably posed information state problem is optimal for the original problem. The proposed approach is tested on various different systems, and the performance is compared with state-of-the-art LTV system identification techniques.

Deep Neural Network (DNN)-based video analytics significantly improves recognition accuracy in computer vision applications. Deploying DNN models at edge nodes, closer to end users, reduces inference delay and minimizes bandwidth costs. However, these resource-constrained edge nodes may experience substantial delays under heavy workloads, leading to imbalanced workload distribution. While previous efforts focused on optimizing hierarchical device-edge-cloud architectures or centralized clusters for video analytics, we propose addressing these challenges through collaborative distributed and autonomous edge nodes. Despite the intricate control involved, we introduce EdgeVision, a Multiagent Reinforcement Learning (MARL)- based framework for collaborative video analytics on distributed edges. EdgeVision enables edge nodes to autonomously learn policies for video preprocessing, model selection, and request dispatching. Our approach utilizes an actor-critic-based MARL algorithm enhanced with an attention mechanism to learn optimal policies. To validate EdgeVision, we construct a multi-edge testbed and conduct experiments with real-world datasets. Results demonstrate a performance enhancement of 33.6% to 86.4% compared to baseline methods.

Lossless image compression is an essential research field in image compression. Recently, learning-based image compression methods achieved impressive performance compared with traditional lossless methods, such as WebP, JPEG2000, and FLIF. However, there are still many impressive lossy compression methods that can be applied to lossless compression. Therefore, in this paper, we explore the methods widely used in lossy compression and apply them to lossless compression. Inspired by the impressive performance of the Gaussian mixture model (GMM) shown in lossy compression, we generate a lossless network architecture with GMM. Besides noticing the successful achievements of attention modules and autoregressive models, we propose to utilize attention modules and add an extra autoregressive model for raw images in our network architecture to boost the performance. Experimental results show that our approach outperforms most classical lossless compression methods and existing learning-based methods., Comment: 5 pages

Exploiting label correlations is important to multi-label classification. Previous methods capture the high-order label correlations mainly by transforming the label matrix to a latent label space with low-rank matrix factorization. However, the label matrix is generally a full-rank or approximate full-rank matrix, making the low-rank factorization inappropriate. Besides, in the latent space, the label correlations will become implicit. To this end, we propose a simple yet effective method to depict the high-order label correlations explicitly, and at the same time maintain the high-rank of the label matrix. Moreover, we estimate the label correlations and infer model parameters simultaneously via the local geometric structure of the input to achieve mutual enhancement. Comparative studies over twelve benchmark data sets validate the effectiveness of the proposed algorithm in multi-label classification. The exploited high-order label correlations are consistent with common sense empirically. Our code is publicly available at https://github.com/Chongjie-Si/HOMI., Comment: 2023, TKDE

Clostridium perfringens is an important pathogen for both humans and animals, causing human foodborne disease and necrotic enteritis in poultry. In the present study, a C. perfringens-specific phage, vB_CpeS_BG3P (designated as BG3P hereafter), was isolated from chicken farm sewage. Both electron microscopy and phylogenetic analysis suggested that phage BG3P is a novel phage belonging to Siphoviridae family. Phage BG3P exhibited a broad host range against different C. perfringens isolates (90.63% of strains were infected). Sequencing of the complete genome revealed a linear double-stranded DNA (43,528 bp) with 28.65% GC content. After sequence analysis, 73 open reading frames (orf s) were predicted, of which only 13 were annotated with known functions. No tRNA and virulence encoding genes were detected. It should be noted that the protein of orf 15 has 97.92% homology to C. perfringens-specific chloramphenicol resistance protein, which has not been reported for any C. perfringens phage. Phylogenetic analysis of the ssDNA binding protein demonstrated that this phage is closely related to C. perfringens phages phiSM101 and phi3626. In considering future use as an antimicrobial agent, some biological characteristics were observed, such as a good pH (3–11) stability and moderate temperature tolerance (<60 C). Moreover, bacteriophage BG3P showed a good antimicrobial effect against C. perfringens liquid cultures. Thus, phage treatment with MOI ≥ 100 completely inhibited bacterial growth compared to untreated cultures. Although phage BG3P shows good lytic efficiency and broad host range in vitro, future development and application may need to consider removal of the chloramphenicol-like resistance gene or exploring its lysin for future antibacterial applications.

Solar-induced chlorophyll fluorescence (SIF) has been widely used to track vegetation photosynthesis at different scales ranging from in-situ measurements to satellite products. Airborne platforms sample SIF data at a spatial scale intermediate between in-situ and satellite, matching that of ground measurement (e.g. flux tower footprints and other field sampling), enabling us to explore causes of SIF variation and validate satellite-based SIF products. However, harmonizing SIF across sensors and platforms (correcting for systematic errors to yield a consistent, comparable SIF product) is challenging because SIF can be retrieved in different absorption windows, with different instruments and methods complicating the comparison between different observational levels (i.e., ground, airborne, satellites) and between sites equipped with different instruments with varying optical properties (spectral resolution and sampling intervals, spatial resolution). Additionally, the spatial and temporal variability of atmospheric properties can influence the retrieval of the weak SIF signal. Because of these complications, direct comparisons of airborne and ground SIF across scales are rarely attempted. In this study, we combined airborne SIF data with simultaneous ‘ground truth’ data collected by stationary and mobile platforms in a soybean field in Nebraska, USA. In this effort, we tested several SIF extraction methods, including Fraunhofer Line Discrimination (FLD), improved Fraunhofer Line Discrimination (iFLD), Spectral Fitting Method (SFM), SpecFit, and a Singular Vector Decomposition (SVD) method. The SpecFit method was sensitive to the 715–740 nm water bands and removing the water bands in the fitting process yielded better agreement between the airborne and ground SIF spectra. Accurate estimation of the ground level downwelling irradiance obtained by ground measurements over a calibration target improved agreement between airborne and ground SIF retrievals at the O2A band

Ensemble clustering integrates a set of base clustering results to generate a stronger one. Existing methods usually rely on a co-association (CA) matrix that measures how many times two samples are grouped into the same cluster according to the base clusterings to achieve ensemble clustering. However, when the constructed CA matrix is of low quality, the performance will degrade. In this paper, we propose a simple yet effective CA matrix self-enhancement framework that can improve the CA matrix to achieve better clustering performance. Specifically, we first extract the high-confidence (HC) information from the base clusterings to form a sparse HC matrix. By propagating the highly-reliable information of the HC matrix to the CA matrix and complementing the HC matrix according to the CA matrix simultaneously, the proposed method generates an enhanced CA matrix for better clustering. Technically, the proposed model is formulated as a symmetric constrained convex optimization problem, which is efficiently solved by an alternating iterative algorithm with convergence and global optimum theoretically guaranteed. Extensive experimental comparisons with twelve state-of-the-art methods on eight benchmark datasets substantiate the effectiveness, flexibility and efficiency of the proposed model in ensemble clustering. The codes and datasets can be downloaded at https://github.com/Siritao/EC-CMS.

Recent advances of Transformers have brought new trust to computer vision tasks. However, on small dataset, Transformers is hard to train and has lower performance than convolutional neural networks. We make vision transformers as data-efficient as convolutional neural networks by introducing multi-focal attention bias. Inspired by the attention distance in a well-trained ViT, we constrain the self-attention of ViT to have multi-scale localized receptive field. The size of receptive field is adaptable during training so that optimal configuration can be learned. We provide empirical evidence that proper constrain of receptive field can reduce the amount of training data for vision transformers. On Cifar100, our ViT-P Base model achieves the state-of-the-art accuracy (83.16%) trained from scratch. We also perform analysis on ImageNet to show our method does not lose accuracy on large data sets.