Rare Objects Research Articles

Unsupervised pseudoinverse hashing learning model for rare astronomical object retrieval

Unsupervised pseudoinverse hashing learning model for rare astronomical object retrieval

Social isolation trajectories in midlife and later-life: patterns and associations with health.

Social isolation has objective and subjective dimensions. Few studies have simultaneously examined trajectories of both dimensions. We integrated multiple indicators of both dimensions to identify social isolation trajectory patterns and investigated how different patterns were related to adults' physical, mental, cognitive, and self-rated health. We used latent class growth modeling to examine social isolation trajectory patterns, based on data from the 2008-2016 waves of the Health and Retirement Study (N = 6457). Mixed-effect linear models were used to examine how trajectory patterns were associated with functional limitations, depressive symptoms, memory deficits, and self-rated health over the 8-year study period. Four social isolation trajectory patterns were identified: severe isolation (15.4%), moderate isolation (37.6%), some objective and rare subjective isolation (35.4%), and rare objective and low subjective isolation (11.6%). Social isolation trajectory patterns showed a gradient in all health domains. The rare objective and low subjective isolation group had the best health (i.e., the fewest functional limitations, depressive symptoms, and memory deficits and the best self-rated health); the some objective and rare subjective isolation group had the next best health; the moderate isolation group had the second worst health; and the severe isolation group had the worst health. The prevalence and stability of severe and moderate social isolation suggest it may be necessary to address social isolation at the national level. The most favorable health outcomes associated with the rare objective and low subjective isolation group supports interventions to strengthen social networks and engagement midlife and later-life.

Classifying Galaxy Morphologies with Few-shot Learning

Abstract The taxonomy of galaxy morphology is critical in astrophysics as the morphological properties are powerful tracers of galaxy evolution. With the upcoming Large-scale Imaging Surveys, billions of galaxy images challenge astronomers to accomplish the classification task by applying traditional methods or human inspection. Consequently, machine learning, in particular supervised deep learning, has been widely employed to classify galaxy morphologies recently due to its exceptional automation, efficiency, and accuracy. However, supervised deep learning requires extensive training sets, which causes considerable workloads; also, the results are strongly dependent on the characteristics of training sets, which leads to biased outcomes potentially. In this study, we attempt Few-shot Learning to bypass the two issues. Our research adopts the data set from the Galaxy Zoo Challenge Project on Kaggle, and we divide it into five categories according to the corresponding truth table. By classifying the above data set utilizing few-shot learning based on Siamese Networks and supervised deep learning based on AlexNet, VGG_16, and ResNet_50 trained with different volumes of training sets separately, we find that few-shot learning achieves the highest accuracy in most cases, and the most significant improvement is 21% compared to AlexNet when the training sets contain 1000 images. In addition, to guarantee the accuracy is no less than 90%, few-shot learning needs ∼6300 images for training, while ResNet_50 requires ∼13,000 images. Considering the advantages stated above, foreseeably, few-shot learning is suitable for the taxonomy of galaxy morphology and even for identifying rare astrophysical objects, despite limited training sets consisting of observational data only.

The symbiotic X-ray binaries Sct X-1, 4U 1700+24, and IGR J17329−2731

ABSTRACT Symbiotic X-ray binaries are systems hosting a neutron star accreting form the wind of a late-type companion. These are rare objects and so far only a handful of them are known. One of the most puzzling aspects of the symbiotic X-ray binaries is the possibility that they contain strongly magnetized neutron stars. These are expected to be evolutionary much younger compared to their evolved companions and could thus be formed through the (yet poorly known) accretion induced collapse of a white dwarf. In this paper, we perform a broad-band X-ray and soft γ-ray spectroscopy of two known symbiotic binaries, Sct X−1 and 4U 1700+24, looking for the presence of cyclotron scattering features that could confirm the presence of strongly magnetized NSs. We exploited available Chandra, Swift, and NuSTAR data. We find no evidence of cyclotron resonant scattering features (CRSFs) in the case of Sct X−1 but in the case of 4U 1700+24 we suggest the presence of a possible CRSF at ∼16 keV and its first harmonic at ∼31 keV, although we could not exclude alternative spectral models for the broad-band fit. If confirmed by future observations, 4U 1700+24 could be the second symbiotic X-ray binary with a highly magnetized accretor. We also report about our long-term monitoring of the last discovered symbiotic X-ray binary IGR J17329−2731 performed with Swift/XRT. The monitoring revealed that, as predicted, in 2017 this object became a persistent and variable source, showing X-ray flares lasting for a few days and intriguing obscuration events that are interpreted in the context of clumpy wind accretion.

Fossilization of Precambrian microfossils in the Volyn pegmatite, Ukraine

Abstract. We report on Precambrian microfossils from igneous rocks of the Volyn pegmatite district, associated with the Paleoproterozoic Korosten pluton, northwestern Ukraine. The fossils were recovered from meter-sized miarolitic cavities and show a well-preserved 3D morphology, mostly filamentous but with a large variety of types and also in irregular, flaky shapes reminiscent of former biofilms, as well as rare spherical objects. Based on literature data, pyrolysis experiments, and reflected light microscopy results, the organic matter (OM) is characterized as (oxy-)kerite. Further investigations with microscopic techniques, including scanning and transmission electron microscopy, and electron microprobe analysis show that fossilization likely occurred during a hydrothermal, post-pegmatitic event by silicification dominantly in the outermost 1–2 µm of the microfossils. The hydrothermal fluid, derived from the pegmatitic environment, was enriched in SiF4, Al, Ca, Na, K, Cl, and S. The OM shows O enrichment in which N and S content is low, indicating simultaneous N and S loss during anaerobic oxidation. Mineralization with Al silicates starts at the rim of the microfossils, continuing in its outer parts into identifiable encrustations and intergrowths of clay minerals, feldspar, Ca sulfate, Ca phosphate, Fe sulfide, and fluorite. Breccias, formed during collapse of some the miarolitic cavities, contain decaying OM, which released high concentrations of dissolved NH4+, responsible for the late-stage formation of tobelite-rich muscovite and buddingtonite. The age of the fossils can be restricted to the time between the pegmatite formation, at ∼1.760 Ga, and the breccia formation at ∼1.49 Ga. As the geological environment for the growth of the microorganisms and fossilization, we assume a geyser system in which the essential biological components C, N, S, and P for growth of the organisms in the miarolitic cavities were derived from microorganisms at the surface. Fossilization was induced by magmatic SiF4-rich fluids. The Volyn occurrence is a distinct and uncommon example of Precambrian fossils, and the results underline the importance of cavities in granitic rocks as a possible habitat for microorganisms preserved in the deep biosphere.

Thethesanproject: Lyman-α emission and transmission during the Epoch of Reionization

ABSTRACTThe visibility of high-redshift Lyman-alpha emitting galaxies (LAEs) provides important constraints on galaxy formation processes and the Epoch of Reionization (EoR). However, predicting realistic and representative statistics for comparison with observations represents a significant challenge in the context of large-volume cosmological simulations. The thesan project offers a unique framework for addressing such limitations by combining state-of-the-art galaxy formation (IllustrisTNG) and dust models with the arepo-rt radiation-magnetohydrodynamics solver. In this initial study, we present Lyman-alpha centric analysis for the flagship simulation that resolves atomic cooling haloes throughout a $(95.5\, \text{cMpc})^3$ region of the Universe. To avoid numerical artefacts, we devise a novel method for accurate frequency-dependent line radiative transfer in the presence of continuous Hubble flow, transferable to broader astrophysical applications as well. Our scalable approach highlights the utility of LAEs and red damping-wing transmission as probes of reionization, which reveal nontrivial trends across different galaxies, sightlines, and frequency bands that can be modelled in the framework of covering fractions. In fact, after accounting for environmental factors influencing large-scale ionized bubble formation such as redshift and UV magnitude, the variation across galaxies and sightlines mainly depends on random processes including peculiar velocities and self-shielded systems that strongly impact unfortunate rays more than others. Throughout the EoR local and cosmological optical depths are often greater than or less than unity such that the exp (− τ) behaviour leads to anisotropic and bimodal transmissivity. Future surveys will benefit by targeting both rare bright objects and Goldilocks zone LAEs to infer the presence of these (un)predictable (dis)advantages.

Spectroscopic evolution of very massive stars at Z = 1/2.5 Z⊙

Context. Stars with masses in excess of 100 M⊙ are observed in the Local Universe, but they remain rare objects. Because of the shape of the mass function, they are expected to be present only in the most massive and youngest clusters. They may thus be formed in number in highly star-forming galaxies. Aims. Very massive stars (VMSs) experience strong stellar winds that are stronger than those of their less massive OB-type counterparts. These strong winds therefore need to be taken into account in evolutionary models and synthetic spectra to properly predict the appearance of VMS. Methods. We present evolutionary models computed with the code STAREVOL. They include a recent mass-loss recipe that is relevant for VMSs. We subsequently calculated atmosphere models and synthetic spectra along the resulting tracks with the code CMFGEN. We studied stars with masses between 150 and 400 M⊙ and focused on a metallicity Z = 1/2.5 Z⊙. We studied the impact of our VMS spectra on the spectral energy distribution of young starbursts. Results. We show that the optical and UV range is dominated by He II 4686 and He II 1640 emission for almost the entire main-sequence evolution of VMSs, in contrast to less massive stars. In the UV spectral range, carbon, nitrogen, and iron lines shape the spectra of VMSs, which appear for most of their evolution as WNh objects. The morphology of the synthetic spectra is similar to that of VMSs in the Large Magellanic Cloud. We show that stars with masses higher than 100 M⊙ emit nearly as much light as all other stars in young starbursts. The integrated UV spectrum of these starbursts is significantly affected by the presence of VMSs. Conclusions. We conclude that a consistent treatment of the evolution and the atmospheres of VMSs is mandatory to properly study spatially unresolved regions of intense star formation. We make our synthetic spectra and spectral energy distributions available to the community.

Relic galaxy analogues in TNG50 simulation: the formation pathways of surviving red nuggets in a cosmological simulation

ABSTRACT Relic galaxies are massive compact quiescent galaxies that formed at high-redshift and remained almost unchanged since then. In this work, we search for analogues to relic galaxies in the TNG50 cosmological simulations to understand relic formation and test the ability of TNG50 to reproduce such rare objects. Using stellar mass, age, radius, quiescence, and stellar assembly criteria, we find five subhaloes in TNG50 that could be potential relic analogues. We compare their properties with other constraints imposed by a sample of 13 observed relic galaxies. We find one analogue in TNG50 that simultaneously satisfies most of the available observational constraints, such as metallicity and morphology. It also shows similarities to the confirmed relic NGC 1277, regarding environment and dark matter fraction. By taking into account a degree of relicness, a second relic analogue may also be considered. However, the central parts of the brightness and density profiles of the analogues are less steep than that of real relic galaxies, possibly due to limited numerical resolution. We identify two formation pathways of relic analogues in TNG50 depending on their environment: they either have their remaining gas stripped during the infall into a cluster at z ≲ 1.2 or consume it before z > 1.5. They are then deprived of significant star formation, leaving their stellar populations almost unaltered during the last 9 Gyr. We also find that the analogue progenitors at z ∼ 4 inhabit more massive haloes than progenitors of quiescent galaxies with similar stellar mass at z ∼ 0.

Non-local thermodynamic equilibrium spectral analysis of five hot, hydrogen-deficient pre-white dwarfs

Hot, compact, hydrogen-deficient pre-white dwarfs (pre-WDs) with effective temperatures ofTeff> 70 000 K and a surface gravity of 5.0 < logg< 7.0 are rather rare objects despite recent and ongoing surveys. It is believed that they are the outcome of either single star evolution (late helium-shell flash or late helium-core flash) or binary star evolution (double WD merger). Their study is interesting because the surface elemental abundances reflect the physics of thermonuclear flashes and merger events. Spectroscopically they are divided in three different classes, namely PG1159, O(He), or He-sdO. We present a spectroscopic analysis of five such stars that turned out to have atmospheric parameters in the rangeTeff= 70 000–80 000 K and logg= 5.2–6.3. The three investigated He-sdOs have a relatively high hydrogen mass fraction (10%) that is unexplained by both single (He core flash) and binary evolution (He-WD merger) scenarios. The O(He) star JL 9 is probably a binary helium-WD merger, but its hydrogen content (6%) is also at odds with merger models. We found that RL 104 is the ‘coolest’ (Teff= 80 000 K) member of the PG1159 class in a pre-WD stage. Its optical spectrum is remarkable because it exhibits C IVlines involving Rydberg states with principal quantum numbers up ton= 22. Its rather low mass (0.48−0.02+0.03 M⊙) is difficult to reconcile with the common evolutionary scenario for PG1159 stars due to it being the outcome of a (very) late He-shell flash. The same mass-problem faces a merger model of a close He-sdO plus CO WD binary that predicts PG1159-like abundances. Perhaps RL 104 originates from a very late He-shell flash in a CO/He WD formed by a merger of two low-mass He-WDs.

Be, V, and Cu in the halo star CS 31082-001 from near-UV spectroscopy

ABSTRACT The ‘First Stars’ programme revealed the metal-poor halo star CS 31082-001 to be r-process and actinide rich, including the first measurement of a uranium abundance for an old star. To better characterize and understand such rare objects, we present the first abundance estimates of three elements (Be, V, Cu) for CS 31082-001 from analysis of its near-ultraviolet spectrum. Beryllium is rarely measured in giant stars, and we confirm that its abundance in this star is low due to the rather cool effective temperature that causes destruction of both Be and Li in its atmosphere. Vanadium and copper are iron-peak elements that are starting to be used as chemical-tagging indicators to investigate the origin of stellar populations. We find V and Cu abundances for CS 31082-001 that are comparable to other metal-poor stars, and present new chemical evolution models to investigate our results. In the case of V, extra nucleosynthesis due to interaction of neutrinos with matter is included in the models to be able to reproduce the measured abundance. Given the availability of high-quality spectroscopy of CS 31082-001, we also explore other atomic lines in the near-ultraviolet as a template for future studies of metal-poor stars with the planned CUBES instrument in development for the Very Large Telescope.

Light Antinuclei from the Laboratory to the Cosmos

The antiproton was experimentally discovered at the Bevatron, Berkeley, in 1955, earning Segré and Chamberlain the 1959 Nobel Prize in Physics. After that, light antinuclei, bound states of antiprotons and antineutrons, have been observed in high-energy interactions in the laboratory from antideuteron to antihelium-4 [1]. In nature, antinuclei are extremely rare objects to be found. The search for antinuclei in space has received considerable attention in recent years, following the suggestion that cosmic antinuclei might be produced in the annihilation or decay of dark matter (DM) particles [2]. Alternatively, “secondary” antinuclei could be produced in ordinary high-energy interactions of primary cosmic rays with the interstellar matter in our galaxy. A precise assessment of the background constituted by secondary antinuclei is pivotal for these searches and for the interpretation of the results. The spectrum of antiprotons observed in cosmic rays is consistent with the hypothesis of secondary production. No evidence of primary antiprotons, antihelium, and antideuterons has been found in the cosmic radiation so far. It is clear that the study of the formation of composite antimatter objects cannot but rely on samples of antimatter produced in the laboratory. Comprehensive measurements of different nuclear (and hypernuclear1) species are necessary to meaningfully constrain formation models and require large data samples to be inspected, as the production of nuclear clusters becomes rarer with increasing mass number. Additional fundamental constraints to the production models are obtained from systematic studies of different particle sources, from ­proton–proton (pp) to heavy-ion collisions, where the size of the system can be experimentally controlled based on the number of particles (multiplicity) produced in the collision.

Rare-earth deposits of a non-traditional type in the Azov part of the Ukrainian Shield

The geological structure and prospects of a group of rare earth objects of exogenous origin, unconventional for the Ukrainian industry, are considered. According to the authors, this is mainly the clay weathering crust of granitoids and other aluminosilicate rocks, which contains sorbed or close to them elements of the yttrium group. A feature of ores of this type that may interest investors is the possibility of relatively simple and inexpensive extraction of REE. As an example, a brief description of specific objects within the Azov part of the Ukrainian shield and on its border with Donbas is given. This is the weathering crust of subalkaline rare-metal granites of the Yekateriniv and Starodubiv massifs, aluminosilicate metamorphic rocks of the Valerianiv area, and tectonic mélange zone argillites of the Zhogoliv area. The Y-Ta-Nb type of deposits was established on the massifs, and mainly yttrium-earth deposits on the metamorphic rocks. The actual results of the analytical research made it possible to draw conclusions about the qualitative and quantitative composition of ores and forecast resources. A comparison of industrial technological methods of extracting Y and ∑REE from loose ores of the Zhogoliv ore deposit was made. The expediency of further searches and research in order to expand the mineral raw material rare earth base of Ukraine is substantiated.

Virgin Territories

AbstractIn this wide-ranging conversation, David Serlin (University of California, San Diego) and Roland Betancourt (University of California, Irvine) discuss questions of sexual consent and sexual violence in the visual culture of early Christian art as inspired by Betancourt’s recent book, Byzantine Intersectionality: Sexuality, Gender, and Race in the Middle Ages (2020). Drawing on rare manuscripts and other objects of worship from institutional archives, Betancourt analyzes and contextualizes numerous Byzantine visual texts featuring often confounding representations of sexual acts or gendered behavior that later Christian interpreters would treat as conventional or settled. For Betancourt, early Christian authors and artists were far more open to troubling and experimenting with depictions of sexual and gendered narratives than many medievalists (and, importantly, non-medievalists) have been trained to see.

Probabilistic classification of X-ray sources applied to Swift-XRT and XMM-Newton catalogs

Context. Serendipitous X-ray surveys have proven to be an efficient way to find rare objects, for example tidal disruption events, changing-look active galactic nuclei (AGN), binary quasars, ultraluminous X-ray sources, and intermediate mass black holes. With the advent of very large X-ray surveys, an automated classification of X-ray sources becomes increasingly valuable. Aims. This work proposes a revisited naive Bayes classification of the X-ray sources in the Swift-XRT and XMM-Newton catalogs into four classes – AGN, stars, X-ray binaries (XRBs), and cataclysmic variables (CVs) – based on their spatial, spectral, and timing properties and their multiwavelength counterparts. An outlier measure is used to identify objects of other natures. The classifier is optimized to maximize the classification performance of a chosen class (here XRBs), and it is adapted to data mining purposes. Methods. We augmented the X-ray catalogs with multiwavelength data, source class, and variability properties. We then built a reference sample of about 25 000 X-ray sources of known nature. From this sample, the distribution of each property was carefully estimated and taken as reference to assign probabilities of belonging to each class. The classification was then performed on the whole catalog, combining the information from each property. Results. Using the algorithm on the Swift reference sample, we retrieved 99%, 98%, 92%, and 34% of AGN, stars, XRBs, and CVs, respectively, and the false positive rates are 3%, 1%, 9%, and 15%. Similar results are obtained on XMM sources. When applied to a carefully selected test sample, representing 55% of the X-ray catalog, the classification gives consistent results in terms of distributions of source properties. A substantial fraction of sources not belonging to any class is efficiently retrieved using the outlier measure, as well as AGN and stars with properties deviating from the bulk of their class. Our algorithm is then compared to a random forest method; the two showed similar performances, but the algorithm presented in this paper improved insight into the grounds of each classification. Conclusions. This robust classification method can be tailored to include additional or different source classes and can be applied to other X-ray catalogs. The transparency of the classification compared to other methods makes it a useful tool in the search for homogeneous populations or rare source types, including multi-messenger events. Such a tool will be increasingly valuable with the development of surveys of unprecedented size, such as LSST, SKA, and Athena, and the search for counterparts of multi-messenger events.

Few-Shot Object Detection of Remote Sensing Image via Calibration

Few-shot object detection (FSOD), which aims at detecting rare objects based on few training samples has attracted significant research interest. Previous approaches find that the performance degradation of FSOD is mainly caused by category confusion (high false positives). To solve this issue, we propose a two-stage fine-tuning approach via classification score calibration for remote sensing images, named TFACSC, which follows the flowchart of base training and few-shot fine-tuning to train the detector. First, the backbone with strong representation ability is employed to extract the multi-scale features of the query image. Then, these features are aggregated by a novel multi-head scaled cosine non-local module (MSCN). Next, the aggregated features are used to generate the objectiveness proposals by a region proposal network. Eventually, the generated proposals are refined by a bounding box prediction head for the final category and position prediction, and the category score is calibrated by a novel classification score calibration module (CSCM). Extensive experiments conducted on NWPU VHR 10 and DIOR benchmarks demonstrate the effectiveness of our model. Particularly, for any shot cases, our method greatly outperforms the baseline and achieves state-of-the-art performance.

XtremeAugment: Getting More From Your Data Through Combination of Image Collection and Image Augmentation

Deep convolutional neural networks are highly efficient for computer vision tasks using plenty of training data. However, there remains a problem of small training datasets. For addressing this problem the training pipeline which handles rare object types and an overall lack of training data to build well-performing models that provide stable predictions is required. This article reports on the comprehensive framework <i>XtremeAugment</i> which provides an easy, reliable, and scalable way to collect image datasets and to efficiently label and augment collected data. The presented framework consists of two augmentation techniques that can be used independently and complement each other when applied together. These are Hardware Dataset Augmentation (HDA) and Object-Based Augmentation (OBA). HDA allows the users to collect more data and spend less time on manual data labeling. OBA significantly increases the training data variability and remains the distribution of the augmented images being close to the original dataset. We assess the proposed approach for the apple spoil segmentation scenario. Our results demonstrate a substantial increase in the model accuracy reaching 0.91 F1-score and outperforming the baseline model for up to 0.62 F1-score for a few-shot learning case in the wild data. The highest benefit of applying <i>XtremeAugment</i> is achieved for the cases where we collect images in the controlled indoor environment, but have to use the model in the wild.

300 de ani de la nașterea baronului Samuel von Brukenthal (26 iulie 1721 - 9 aprilie 1803)

"Three Centuries Since Baron Samuel von Brukenthal was Born (26th of July 1721 - 9th of April 1803). Baron Samuel von Brukenthal was an outstanding personality, a man of great erudition and refined taste, whose political career culminated with the dignity of Governor of Transylvania, a dignity he held between 1777 and 1787. Brukenthal was the only Transylvanian Saxon who enjoyed this great honor. Living for many years abroad, he got acquainted with Viennese cultural patterns he tried to implement in his own country. As a Transylvanian representative of the Enlightenment, Brukenthal became famous through his major creation, the first museum in the South Eastern part of Europe opened in 1790 to connoisseurs and foreign travelers and in 1817 to the large public. His fine art collection comprised about 1100 paintings belonging to the major European art schools. Besides paintings he also had a rich collection of etchings in copper, a library consisting of about 16000 volumes, rare archeological objects, as well as a numismatic collection and one of minerals. But his sphere of interest was much wider, including a large scale of sciences, the educational system, the musical life of Sibiu, the art of gardening. Keywords: Brukenthal, baron, politician, governor of Transylvania, Enlightenment, museum, paintings, major European art schools, library, archeological objects, numismatics, minerals. "

Introduction and perspectives of Henomeles culture

The selection fund of Japanese henomeles differs in considerable variety. It was one of the most interesting and rare objects for acclimatization in order to enrich our country мwith plants useful for the national economy. This fruit crop has special genetic and morphological features, due to which it is used in various fields and directions. Therefore, the study of henomeles is quite relevant and requires the development and improvement of various agronomic techniques o cultivation, taking into account the conditions of the region of cultivation of this plant.

Состояние ценопопуляций Tilia cordata и Ulmus glabra в лесах Петрозаводского городского округа

Relevance and purpose. Cenopopulations of deciduous tree species at the northern border of the range are of particular scientific interest as objects of biological diversity. The relevance of the work is associated with the need to organize monitoring of these rare objects in the forests of the Petrozavodsk Urban Okrug by cause of increasing anthropogenic pressure. Assessment of the state of valuable nature conservation objects has not only scientific, but also economic interest in the field of ecosystem services, taking into account those functions of natural ecosystems that ensure the quality of people’s living standards.Material and methods. During 2017–2018 a detailed study of the cenopopulations of Tilia cordata and Ulmus glabra was carried out on two model plots within the boundaries of the Petrozavodsk urban district. The area, abundance, ontogenetic structure of cenopopulations was determined using the standard technique of cenopopulation studies, taking into account the characteristics of specific species. Results and conclusions. The studied cenopopulations are isolated and small (up to 23 hectares). They were forming during the secondary succession anthropogenic felling and fires more than 100 years old. According to the ontogenetic spectrum, cenopopulations are normal mature, have an ontogenetic spectrum with a maximum on immature individuals, thus, cenopopulations are characterized by a normal turnover of generations. Generative reproduction and large generative trees high 16–24 m up to 120 years old are rare for the northern regions.

Size-tunable droplet microfluidic system using an on-chip microfluidic peristaltic pump

Droplet microfluidics has become widely employed in various chemical and biological analyses, by offering the capacity of high-efficiency generation of miniature droplets in accurate sizes and precise concentrations. In this article, a size-tunable droplet microfluidic system has been first developed, which includes an on-chip microfluidic peristaltic pump. In particular, both the sizes and frequencies of the generated droplets can be fine-tuned without requirement of changing the geometrical design of the microfluidic chip itself. By choosing proper parameters as driving voltage and frequency of the peristaltic pump, the desired droplet length (from 81.5 µm to 345.5 µm) and generation frequency can be easily obtained. Due to the on-chip design of the micropump, the size-tunable droplet microfluidic system has tiny dead volume as low as 1 μL. Moreover, less than 200nL reagent was wasted before getting into a stable droplet generating state, showing potential in the applications of capsulation of rare objects in small-volume sample and isovolumetric isolation for precise analysis.