Modulating Nucleation and Crystal Growth of Tin Perovskite Films for Efficient Solar Cells.

The performance of tin halide perovskite solar cells (PSCs) has been severely limited by the rapid crystallization of tin perovskites, which usually leads to an undesirable film quality. In this work, we tackle this issue by regulating the nucleation and crystal growth of tin perovskite films using a small Lewis base additive, urea. The urea-SnI2 interaction facilitates the formation of larger and more uniform clusters, thus accelerating the nucleation process. Additionally, the crystal growth process is extended, resulting in a high-quality tin perovskite film with compact morphology, increased crystallinity, and reduced defects. Consequently, the efficiency of tin PSCs is significantly increased from 10.42% to 14.22%. This work highlights the importance of manipulating the nucleation and crystal growth of tin perovskites to realize efficient tin PSCs.

Homogenizing The Low-Dimensional Phases for Stable 2D-3D Tin Perovskite Solar Cells.

2D-3D tin-based perovskites are considered as promising candidates for achieving efficient lead-free perovskite solar cells (PSCs). However, the existence of multiple low-dimensional phases formed during the film preparation hinders the efficient transport of charge carriers. In addition, the non-homogeneous distribution of low-dimensional phases leads to lattice distortion and increases the defect density, which are undesirable for the stability of tin-based PSCs. Here, mixed spacer cations [diethylamine (DEA+) and phenethylamine (PEA+)] are introduced into tin perovskite films to modulate the distribution of the 2D phases. It is found that compared to the film with only PEA+, the combination of DEA+ and PEA+ favors the formation of homogeneous low-dimensional perovskite phases with three octahedral monolayers (n = 3), especially near the bottom interface between perovskite and hole transport layer. The homogenization of 2D phases help improve the film quality with reduced lattice distortion and released strain. With these merits, the tin PSC shows significantly improved stability with 94% of its initial efficiency retained after storing in a nitrogen atmosphere for over 4600 h, and over 80% efficiency maintained after continuous illumination for 400 h.

Ambient Air Processed Inverted Inorganic Perovskite Solar Cells with over 21 % Efficiency Enabled by Multifunctional Ethacridine Lactate.

All-inorganic cesium lead triiodide perovskites (CsPbI3) have attracted increasing attention due to their good thermal stability, remarkable optoelectronic properties, and adaptability in tandem solar cells. However, N2-filled glovebox is generally required to strictly control the humidity during film fabrication due to the moisture-induced black-to-yellow phase transition, which remains a great hinderance for further commercialization. Herein, we report an effective approach via incorporating multifunctional ethacridine lactate (EAL) to mitigate moisture invasion and enable the fabrication of efficient inverted (p-i-n) CsPbI3 perovskite solar cells (PSCs) under ambient condition. It is revealed that the lactate anions accelerate the crystallization of CsPbI3, shortening the exposure time to moisture during film fabrication. Meanwhile, the conjugated backbone and multiple functional groups in the ethacridine cations can interact with I- and Pb2+ to reduce the undesired defects, stabilize the perovskite structure and facilitate the charge transport in the film. Moreover, EAL incorporation also leads to better energy alignment, thus favoring charge extraction at both upper and bottom interfaces. Consequently, the device efficiency and stability are enormously enhanced, with the champion efficiency reaching 21.08 %. This even surpasses the highest value reported for the devices fabricated in glovebox, representing a record efficiency of inverted all-inorganic PSCs.

A High Time-Efficient Missing Tag Detection Scheme for Integrated RFID Systems.

Missing tag incidents are common in RFID-enabled supply-chain and warehousing scenarios due to cargo theft and employee error operations, which may lead to serious economic losses or potential safety hazards. On the premise of ensuring the accuracy of missing tag detection, this paper aims to improve the time efficiency in an integrated RFID system. Unlike prior work focusing on detecting missing items from a large number of homogeneous tags that are monitored by a single reader, one integrated RFID system possesses multiple readers to communicate with the heterogeneous tags, which have different categorical attributes. In addition, the prior work required repeating the execution several times to capture the missing tags in assorted categories, which is of low time efficiency. Thus, a protocol called Multi-reader Missing Tag Detection (MMTD) is proposed to capture the missing tag quickly and reliably, which can detect missing tags from different categories in a parallel manner and is much more time-efficient than previous work. MMTD has two major advantages compared to prior work: (i) It leverages the knowledge of the spatial distribution of tags to divide up a difficult detection task into several lightweight tasks, which are shared by multiple readers. (ii) It personalizes the time frame of the reader based on the tag population to optimize the utilization of the communication channel. The final simulation results reveal that MMTD is the best in time-efficiency among the comparison protocols, and MMTD outperforms the other missing tag detection protocols by at least 1.5× in the Integrated RFID scenarios.

Comparison of Standard Suture vs Barbed Suture for Closing the Porcine Knee Joint: Evaluation of Biomechanical Integrity and Permeability.

BACKGROUND: This study aimed to compare the biomechanical strength and permeability of barbed vs traditional suture for closure of the porcine knee joint. METHODS: This study used Duroc pig knee joints. For each specimen, a 5-cm medial parapatellar arthrotomy was performed with the knee at 30° of flexion. We closed the arthrotomy wound using barbed suture (size 1/0 V-Loc 180) or traditional suture (size 1/0 PDS II). Specimens were divided into a PDS II (n = 9) and a V-Loc group (n = 9) for biomechanical testing, and a PDS II (n = 9) and a V-Loc group (n = 9) for permeability testing. In biomechanical testing, a continuous load was applied and the wound was pulled apart at 50 mm/min. We compared the maximum load under which each suture type could maintain wound closure. In permeability testing, the knee joints were flexed and extended for 200 cycles at 0.5 Hz from 0° to 120° of flexion. A tube was fixed in the articular cavity of the specimen and connected to a 1.5-m high water capsule. The time taken to wound effusion was compared. RESULTS: There was no significant difference between the mean load at initial failure for PDS II (424 ± 192 N) vs V-Loc (471 ± 100 N, P = .529), or between the mean time until effusion for PDS II (6.8 ± 3.4 seconds) vs V-Loc (5.5 ± 2.5 seconds, P = .390). CONCLUSION: Standard and barbed suture had similar wound holding strength and permeability. The barbed suture was as stable as traditional suture.

[Effects of stocking density and exchanging water frequency on growth and inner quality of Whitmania pigra].

The effects of stocking density and exchanging water frequency on growth, digestive enzyme activity, anti-oxidative enzyme and inner quality of Whitmania pigra Whitman were evaluated with corresponding measures. The results showed that the eventual biomass, specific growth rate, gained weight rate, activities of amylase, lipase, protease, SOD, CAT, and ALP correlated positively with stocking density and negatively with exchanging water frequency (P<0.05). Exchanging water frequency had negative correlation with ammonia nitrogen, nitrite, and hydrogen sulfide while revealed positive correlation with dissolved oxygen in the water. Stocking density and exchanging water frequency showed no significant effects on the contents of moisture, total ash, and acid-insoluble ash. It suggested that the optimum stocking density was 7.5 million per hectare and the appropriate exchanging water interval was 72 h.

[Downregulation of 53BP1 by short hairpin RNA enhances radiosensitivity in laryngeal carcinoma cells].

OBJECTIVE: To determine the effect of downregulation of 53BP1 expression on cell growth and radiosensitivity in laryngeal carcinoma Hep-2 cells. METHODS: HEP-2 cell lines were established with a stable knockdown of 53BP1 with short hairpin RNA (shRNA). The level of expressed protein of negative control group (NC),wild type Hep-2 and downregulation of 53BP1 (P6) group was determined by Western blotting. Proliferation on normal conditions was detected by MTT. Radiosensitivity and growth of cells were detected by flow cytometry. RESULTS: A stable 53BP1 downregulated cell line P6 was established. Similar cell growth was observed between the 53BP1 downregulated cells and the control cells. The downregulation of 53BP1 reduced the number of clonogenic cells exposed to radiation. Compared with wild type Hep-2 group and NC group, Western blot results showed a decrease in 53BP1 protein level in P6 group (P < 0.05), reducing the ratio of arrest of G2/M with radiation dose increased (P < 0.05). MTT results revealed the lower 53BP1 protein level did not affect the cell proliferation. After exposure to 0, 2, 6, 10 Gy ionizing radiation (IR), P6 cells had lower, radiosensitivity parameters (D0, SF2, Dq, N) than controls and wild type Hep-2 (P < 0.05). CONCLUSION: RNA interference could effectively down-regulate the expression of 53BP1 and reduce arrest of G2/M phase, thus enhancing the radiosensitivity of Hep-2 cell line.

Phosphonic Chloride Assisted Fabrication of Highly Emissive Mixed Halide Perovskite Films in Ambient Air for Blue Light-Emitting Diodes.

Blue perovskite light-emitting diodes (LEDs) have emerged as promising candidates for full-color display and lighting applications. However, the fabrication of blue-emitting perovskite films typically requires an inert environment, leading to increased complexity and cost in the manufacturing process, which is undesirable for applications of perovskite LEDs. Herein, we report a strategy to fabricate bright blue-emitting perovskite films in ambient air by incorporating phosphonic chlorides in a perovskite precursor solution. We used two different phosphonic chlorides, diphenylphosphonic chloride (DPPC) and phenylphosphonic dichloride (PPDC), and comparatively studied their effects on the properties of perovskite films and the blue LEDs. It is found that PPDC possesses a stronger chlorination ability due to higher hydrolysis reactivity; meanwhile, it has a stronger interaction with the perovskite compared to DPPC, resulting in an improved film quality and enhanced blue emission with a photoluminescence quantum yield of 45%, which represents the record value for the air-processed blue perovskite films. Blue perovskite LEDs are fabricated, and the emission wavelengths are effectively tuned by controlling the concentration of phosphonic chlorides. Benefiting from the optimized perovskite films with reduced nonradiative recombination and promoted charge injection and transport, the PPDC-derived blue perovskite LEDs exhibit improved performance with an external quantum efficiency of 3.3% and 1.2% for the 490 and 480 nm emission wavelength, respectively.

Multifunctional Buried Interface Modification Enables Efficient Tin Perovskite Solar Cells.

Tin perovskite solar cells (PSCs) are considered promising candidates to promote lead-free perovskite photovoltaics. However, their power conversion efficiency (PCE) is limited by the easy oxidation of Sn2+ and low quality of tin perovskite film. Herein, an ultra-thin 1-carboxymethyl-3-methylimidazolium chloride (ImAcCl) layer is used to modify the buried interface in tin PSCs, which can induce multifunctional improvements and remarkably enhance the PCE. The carboxylate group (CO) and the hydrogen bond donor (NH) in ImAcCl can interact with tin perovskites, thus significantly suppressing the oxidation of Sn2+ and reducing the trap density in perovskite films. The interfacial roughness is reduced, which contributes to a high-quality tin perovskite film with increased crystallinity and compactness. In addition, the buried interface modification can modulate the crystal dimensionality, favoring the formation of large bulk-like crystals instead of low-dimensional ones in tin perovskite films. Therefore, the charge carrier transport is effectively promoted and the charge carrier recombination is suppressed. Eventually, tin PSCs show a remarkably enhanced PCE from 10.12% to 12.08%. This work highlights the importance of buried interface engineering and provides an effective way to realize efficient tin PSCs.

Synergistic Steric Effect of Precursor And Antisolvent Enables Strongly Confined Perovskite Films with Efficient and Spectral Stable Blue Emission.

Reducing the crystal size of perovskites to the strong quantum confinement regime is an effective way to realize blue luminescence for light-emitting applications. However, challenges remain in directly constraining the crystal growth during film preparation to achieve three-dimensional quantum confinement, and the widely used long-chain ligands may bring difficulties for charge transport and unfavorably affect the device performance. Herein, we report a novel strategy for fabricating strongly confined blue-emitting perovskite nanocrystalline films via synergistic steric effect modulation by precursors and antisolvents. We synthesize cesium pentafluoropropanoate (CsPFPA) as a new type of precursor agent, where the steric effect of the PFPA group can help constrain the growth of perovskite crystals and passivate the defects. Furthermore, different types of antisolvents with varied molecular sizes and steric hindrance are used to regulate the size of perovskite crystals and improve film quality. Consequently, highly emissive blue perovskite films are realized with the emission wavelength effectively tuned in the blue region by varying the concentration of CsPFPA as well as the type of antisolvents. Based on the strongly confined perovskite films, blue light-emitting diodes (LEDs) are constructed, showing good spectral tunability and stability in the electroluminescence. This work demonstrates a novel pathway for developing bright perovskite blue emitters for LEDs, which may potentially advance their future applications in display and lighting.

Automated segmentation of cell organelles in volume electron microscopy using deep learning.

Recent advances in computing power triggered the use of artificial intelligence in image analysis in life sciences. To train these algorithms, a large enough set of certified labeled data is required. The trained neural network is then capable of producing accurate instance segmentation results that will then need to be re-assembled into the original dataset: the entire process requires substantial expertise and time to achieve quantifiable results. To speed-up the process, from cell organelle detection to quantification across electron microscopy modalities, we propose a deep-learning based approach for fast automatic outline segmentation (FAMOUS), that involves organelle detection combined with image morphology, and 3D meshing to automatically segment, visualize and quantify cell organelles within volume electron microscopy datasets. From start to finish, FAMOUS provides full segmentation results within a week on previously unseen datasets. FAMOUS was showcased on a HeLa cell dataset acquired using a focused ion beam scanning electron microscope, and on yeast cells acquired by transmission electron tomography. RESEARCH HIGHLIGHTS: Introducing a rapid, multimodal machine-learning workflow for the automatic segmentation of 3D cell organelles. Successfully applied to a variety of volume electron microscopy datasets and cell lines. Outperforming manual segmentation methods in time and accuracy. Enabling high-throughput quantitative cell biology.

Relationship Between Mindfulness and Affiliate Stigma in Parents of Children with Autism Spectrum Disorder in China: The Mediating Role of Coping Styles.

PURPOSE: This study aims to investigate the current status of affiliate stigma among parents of autistic children, analyze the influencing factors, explore the relationship among mindfulness, coping styles, and affiliate stigma, and verify the mediating role of coping styles between mindfulness and affiliate stigma in parents of children with autism in China. METHOD: Between February and April 2023, the Child Development Behaviour Centre of a public hospital in China recruited 345 parents of children with autism. These parents completed the general information questionnaire, the Mindful Attention Awareness Scale, the Affiliate Stigma Scale, and the Simple Coping Style Questionnaire. We then adapted the Hayes Process Macro and Bootstrap methods to examine the mediating effects of coping styles between mindfulness and affiliate stigma. RESULTS: (1) The total affiliate stigma score of parents of children with autism was 48.53 (standard deviation:: 10.74). Parents' age, monthly family income, duration of care, mindfulness, and coping styles were the influencing factors of parental affiliate stigma. (2) Mindfulness was positively correlated with positive coping style (r = 0.33, p < .01) and negatively correlated with negative coping style, affiliate stigma (r = -0.38, -0.39, p < .01), whereas affiliate stigma was negatively correlated with positive coping style (r = -0.34, p < .01) and positively correlated with negative coping style (r = 0.41, p < .01). (3) Positive coping style and negative coping style play a parallel mediating role between mindfulness and affiliate stigma of parents of autistic children. CONCLUSIONS: Parents of children with autism experience significant levels of affiliate stigma. Mindfulness has a direct impact on associated stigma in parents of children with autism and also indirectly predicts associated stigma through the intermediary influence of positive and negative coping styles. Healthcare professionals could perform mindfulness interventions from an optimistic psychology viewpoint to boost parents' mindfulness and coping abilities, thereby accomplishing the objective of mitigating affiliate stigma.

Zabramski classification in predicting the occurrence of symptomatic intracerebral hemorrhage in sporadic cerebral cavernous malformations.

OBJECTIVE: The authors aimed to investigate the evolutionary characteristics of the Zabramski classification of cerebral cavernous malformations (CCMs) and the value of the Zabramski classification in predicting clinical outcome in patients with sporadic CCM. METHODS: This retrospective study consecutively included cases of sporadic CCM that had been untreated from January 2001 through December 2021. Baseline and follow-up patient information was recorded. The evolution of the Zabramski classification of a sporadic CCM was defined as the initial lesion type changing into another type for the first time on MRI follow-up. The primary outcome was the occurrence of a hemorrhage event, which was defined as a symptomatic event with radiological evidence of overt intracerebral hemorrhage. RESULTS: Among the 255 included cases, 55 (21.6%) were classified as type I CCM, 129 (50.6%) as type II CCM, and 71 (27.8%) as type III CCM, based on initial MRI. During a mean follow-up of 58.8 ± 33.6 months, 51 (20.0%) patients had lesion classification transformation, whereas 204 (80.0%) patients maintained their initial type. Among the 51 transformed lesions, 29 (56.9%) were type I, 11 (21.6%) were type II, and 11 (21.6%) were type III. Based on all follow-up imaging, of the initial 55 type I lesions, 26 (47.3%) remained type I and 27 (49.1%) regressed to type III because of hematoma absorption; 91.5% of type II and 84.5% of type III lesions maintained their initial type during MRI follow-up. The classification change rate of type I lesions was statistically significantly higher than those of type II and III lesions. After a total follow-up of 1157.7 patient-years, new clinical hemorrhage events occurred in 40 (15.7%) patients. The annual cumulative incidence rate for symptomatic hemorrhage in all patients was 3.4 (95% CI 2.5-4.7) per 100 person-years. Kaplan-Meier survival analysis showed that the annual cumulative incidence rate for symptomatic hemorrhage of type I CCM (15.3 per 100 patient-years) was significantly higher than those of type II (0.6 per 100 patient-years) and type III (2.3 per 100 patient-years). CONCLUSIONS: This study suggests that the Zabramski classification is helpful in estimating clinical outcome and can assist with surgical decision-making in patients with sporadic CCM.

Object Detection Based on Swin Deformable Transformer-BiPAFPN-YOLOX.

Object detection technology plays a crucial role in people's everyday lives, as well as enterprise production and modern national defense. Most current object detection networks, such as YOLOX, employ convolutional neural networks instead of a Transformer as a backbone. However, these techniques lack a global understanding of the images and may lose meaningful information, such as the precise location of the most active feature detector. Recently, a Transformer with larger receptive fields showed superior performance to corresponding convolutional neural networks in computer vision tasks. The Transformer splits the image into patches and subsequently feeds them to the Transformer in a sequence structure similar to word embeddings. This makes it capable of global modeling of entire images and implies global understanding of images. However, simply using a Transformer with a larger receptive field raises several concerns. For example, self-attention in the Swin Transformer backbone will limit its ability to model long range relations, resulting in poor feature extraction results and low convergence speed during training. To address the above problems, first, we propose an important region-based Reconstructed Deformable Self-Attention that shifts attention to important regions for efficient global modeling. Second, based on the Reconstructed Deformable Self-Attention, we propose the Swin Deformable Transformer backbone, which improves the feature extraction ability and convergence speed. Finally, based on the Swin Deformable Transformer backbone, we propose a novel object detection network, namely, Swin Deformable Transformer-BiPAFPN-YOLOX. experimental results on the COCO dataset show that the training period is reduced by 55.4%, average precision is increased by 2.4%, average precision of small objects is increased by 3.7%, and inference speed is increased by 35%.

Fabrication of Highly Luminescent Quasi Two-Dimensional CsPbBr3 Perovskite Films in High Humidity Air for Light-Emitting Diodes.

Perovskite light-emitting diodes (LEDs) have attracted extensive attention in recent years due to their outstanding performance and promise in lighting and display applications. However, the fabrication of perovskite LEDs usually requires a low-humidity atmosphere, which is unfavorable for industrial production. Herein, we report an effective strategy to fabricate highly luminescent quasi two-dimensional CsPbBr3 perovskite films in an ambient atmosphere with a humidity up to 60%. We reveal that the hole transport layer (HTL) plays a significant role in the morphology and optical properties of the perovskite films. Using hydrophobic self-assembled monolayer materials as HTLs can remarkably improve the quality of the perovskite films processed in high humidity air. The resultant perovskite LEDs show reduced leakage current and significantly enhanced performance. Furthermore, surface treatment is conducted to prevent water invasion and promote radiative recombination in perovskite films and LEDs. Eventually, the perovskite LEDs exhibit bright green emission with an external quantum efficiency of 4.87%. The present work provides a feasible pathway to overcome the humidity limitation for obtaining bright perovskite films and LEDs, which would contribute to further reducing the fabrication cost of perovskite LEDs and promoting their applications.

Cascading effects of Pb on the environmental and symbiotic microbiota and tadpoles' physiology based on field data and laboratory validation.

Heavy metal pollution poses a serious threat to ecosystems. Currently, there is a lack of field data that would enable us to gain a systematic understanding of the influences of heavy metals on aquatic ecosystems, especially the interactions between environments and animals. We studied the relationships between the variations in heavy metal concentrations (10 species including Pb in sediments and surface water), the community structure of environmental and symbiotic microbiota, and the gut traits of Bufo gargarizans tadpoles across 16 sampling sites on the Chengdu Plain through rigorous statistical analysis and laboratory validation. The results show that heavy metal concentrations, especially the Pb concentration of the sediment, are linked to the variations in sediment and tadpoles' gut microbiomes but not to water microbiota. For the sediment microbiota, Pb causes a trade-off between the proportions of Burkholderiales and Verrucomicrobiae and affects the methane, sulfide, and nitrate metabolisms. For tadpoles, a high sediment Pb content leads to a low abundance of gut aerobic bacteria and a large relative gut weight under both field and laboratory conditions. In addition, Pb promotes the growth of B. gargarizans tadpoles under laboratory conditions. These effects seem to be beneficial to tadpoles. However, a high Pb content leads to a low abundance of probiotic bacteria (e.g., Verrucomicrobiae, Eubacteriaceae, and Cetobacterium) and a high abundance of pathogenic bacteria in the gut and environment, suggesting potential health risks posed by Pb. Interestingly, there is a causal relationship between Pb-induced variations in sediment and symbiotic microbiotas, and the latter is further linked to the variation in relative gut weight of tadpoles. This suggests a cascading effect of Pb on the ecosystem. In conclusion, our results indicate that among the heavy metals, the Pb in sediment is a critical factor affecting the aquatic ecosystem through an environment-gut-physiology pathway mediated by microbiota.

Control of n-Phase Distribution in Quasi Two-Dimensional Perovskite for Efficient Blue Light-Emitting Diodes.

Pure-bromide quasi-2D perovskite (PBQ-2DP) promises high-performance light-emitting diodes (LEDs), while a challenge remains on control over its n-phase distribution for bright true-blue emission. Present work addresses the challenge through exploring the passivation molecule of amino acid with reinforced binding energy, which generates narrow n-phase distribution preferentially at n = 3 with true blue emission at 478 nm. Consequently, a peak external quantum efficiency of 5.52% and a record brightness of 512 cd m-2 are achieved on the PBQ-2DP-based true blue PeLED, these both values located among the top in the records of similar devices. We further reveal that the electron-phonon coupling results in the red-shifted emission in the PBQ-2DP film, suggesting that the view of n-phase distribution dominated true-blue emission in PBQ-2DP needs to be revisited, pointing out a guideline of electron-phonon coupling suppression to relieve the strait of realizing true blue or even deep blue emission in the PBQ-2DP film.

Intravenous leiomyomatosis: CT findings.

Intravenous leiomyomatosis (IVL) is a rare smooth muscle tumor. Although IVL is histologically benign, it might be aggressive in its behavior and can grow into pelvic veins and the inferior vena cava (IVC) extending into the heart chambers and pulmonary vasculature. Occasionally, it was found to have lung metastasis. We describe four cases of IVL in the IVC with a history of hysterectomy for uterine leiomyoma, one extending into the left renal vein and three growing into the right heart chamber. We report the computed tomography (CT) findings in the four cases and briefly discuss the CT features of IVL in order to help making accurately preoperative diagnosis and improve the rate of surgical resection and survival.

A tumor suppressive coactivator complex of p53 containing ASC-2 and histone H3-lysine-4 methyltransferase MLL3 or its paralogue MLL4.

ASC-2, a multifunctional coactivator, forms a steady-state complex, named ASCOM (for ASC-2 COMplex), that contains the histone H3-lysine-4 (H3K4)-methyltransferase MLL3 or its paralogue MLL4. Somewhat surprisingly, given prior indications of redundancy between MLL3 and MLL4, targeted inactivation of the MLL3 H3K4-methylation activity in mice is found to result in ureter epithelial tumors. Interestingly, this phenotype is exacerbated in a p53(+/-) background and the tumorigenic cells are heavily immunostained for gammaH2AX, indicating a contribution of MLL3 to the DNA damage response pathway through p53. Consistent with the in vivo observations, and the demonstration of a direct interaction between p53 and ASCOM, cell-based assays have revealed that ASCOM, through ASC-2 and MLL3/4, acts as a p53 coactivator and is required for H3K4-trimethyation and expression of endogenous p53-target genes in response to the DNA damaging agent doxorubicin. In support of redundant functions for MLL3 and MLL4 for some events, siRNA-mediated down-regulation of both MLL3 and MLL4 is required to suppress doxorubicin-inducible expression of several p53-target genes. Importantly, this study identifies a specific H3K4 methytransferase complex, ASCOM, as a physiologically relevant coactivator for p53 and implicates ASCOM in the p53 tumor suppression pathway in vivo.

Scalable Distributed Hashing for Approximate Nearest Neighbor Search.

Hashing has been widely applied to the large-scale approximate nearest neighbor search problem owing to its high efficiency and low storage requirement. Most investigations concentrate on learning hashing methods in a centralized setting. However, in existing big data systems, data is often stored across different nodes. In some situations, data is even collected in a distributed manner. A straightforward way to solve this problem is to aggregate all the data into the fusion center to obtain the search result (aggregating method). However, this strategy is not feasible because of the prohibitive communication cost. Although a few distributed hashing methods have been proposed to reduce this cost, they only focus on designing a distributed algorithm for a specific global optimization objective without considering scalability. Moreover, existing distributed hashing methods aim at finding a distributed solution to hashing, meanwhile avoiding accuracy loss, rather than improving accuracy. To address these challenges, we propose a Scalable Distributed Hashing (SDisH) model in which most existing hashing methods can be extended to process distributed data with no changes. Furthermore, to improve accuracy, we utilize the search radius as a global variable across different nodes to achieve a global optimum search result for every iteration. In addition, a voting algorithm is presented based on the results produced by multiple iterations to further reduce search errors. Theoretical analyses of communication, computation, and accuracy demonstrate the superiority of the proposed model. Numerical simulations on three large-scale and two relatively small benchmark datasets also show that the SDisH model achieves up to 44.75% and 10.23% accuracy gains compared to the aggregating method and state-of-the-art distributed hashing methods, respectively.