Miracle-dz/UniFAR-FTUs huggingface dataset:
Nucleotide Sequence and Expression in Escherichia coli of the Lactococcus lactis Citrate Permease Gene

The plasmid-encoded citrate determinant of the Lactococcus lactis subsp. lactis var. diacetylactis NCDO176 was cloned and functionally expressed in a Cit- Escherichia coli K-12 strain. From deletion derivative analysis, a 3.4-kilobase region was identified which encodes the ability to transport citrate. Analysis of proteins encoded by the cloned fragment in a T7 expression system revealed a 32,000-dalton protein band, which correlated with the ability of cells to transport citrate. Energy-dependent [1,5-'4Cjcitrate transport was found with membrane vesicles prepared from E. coli cells harboring the citrate permease-expressing plasmid. The gene encoding citrate transport activity, citP, was located on the cloned fragment by introducing a site-specific mutation that abolished citrate transport and resulted in a truncated form of the 32,000-dalton expression product. The nucleotide sequence for a 2.2-kilobase fragment that includes the citP gene contained an open reading frame of 1,325 base pairs coding for a very hydrophobic protein of 442 amino acids, which shows no sequence homology with known citrate carriers.
Concordance of Targeted Sequencing from Circulating Tumor DNA and Paired Tumor Tissue for Early Breast Cancer

Simple Summary The VGH-TAYLOR study comprised a subgroup of early-stage breast cancer patients. Targeted sequencing was performed for both fresh-frozen paraffin-embedded (FFPE) tumor tissue and plasma. Common genes interrogated by both platforms were identified, and the concordance between paired targeted sequencing results from the same individual is reported. Only one-quarter of breast cancers were concordant between tumor and liquid biopsy from the same subject. Early-stage breast cancer might shed less circulating tumor DNA (ctDNA) from the tumor and compromise the detectability of liquid biopsy. Abstract In this study, we evaluated the concordance of targeted sequencing between paired ctDNA and matched tumor samples from early breast cancers treated with curative intention. Molecular profiling was performed using the Oncomine Comprehensive Assay v3 and the Oncomine Breast cfDNA Assay v2. The liquid biopsy detection rate was 39% (all-stage breast cancers, n = 612). Among 246 early-stage patients assayed for both ctDNA and matched tumor, the cfDNA assay detected 73 (29.6%) and the comprehensive assay detected 201 (81.7%) breast cancers with at least one alteration (χ2 test, p = 0.001). In total, 67 (25.6%) cases tested positive on both platforms, while the cfDNA and comprehensive assays detected an additional 10 (4%) and 138 (56%) cases, respectively. The most prevalent mutant genes were TP53 (68.3%) and KRAS (53.5%), while the PIK3CA (39.4%), AKT1 (45.9%), and ERBB2 (17.1%) mutations constituted biomarkers for FDA-approved therapeutics. Our study showed that tumor tissue should be the source of actionable mutation detection for early breast cancers, considering that the concordance rate between tumor and liquid biopsy was only one-quarter.
Geometry and Chemistry: Influence of Pore Functionalization on Molecular Transport and Diffusion in Solvent-Filled Zirconium Metal-Organic Frameworks.

Postsynthetic modification (PSM) of metal-organic frameworks (MOFs) enables incorporation of diverse functionalities in pores for chemical separations, drug delivery, and heterogeneous catalysis. However, the effect of PSM on molecular transport, which is essential for most applications of MOFs, has been rarely studied. In this paper, we used perfluoroalkane-functionalized Zr-MOF NU-1008 as a platform to systematically interrogate transport processes and mechanisms in solvated pores. We anchored perfluoroalkanes onto NU-1008 nodes by solvent-assisted ligand incorporation (SALI-n, with n = 3, 5, 7, and 9 denoting the number of fluorinated carbons). Transport of a luminescent molecule, BODIPY, through individual crystallites of four versions of methanol-filled SALI-n was monitored by confocal fluorescence microscopy as a function of time and location. In comparison with the parent NU-1008, the diffusivity of the probe molecules within SALI-n declined by 2- to 7-fold depending on chain length and loading, presumably due to the reduction in pore diameter or adsorptive interactions with perfluoroalkyl chains. Atomistic simulations were performed to uncover the microscopic behavior of the BODIPY diffusion in SALI-n. The perfluoroalkyl chains are observed to stay close to the pore walls, instead of extending toward the pore center. BODIPY molecules, which preferably interact with linkers, were pushed to the interior of the channels as the chain length increased, resulting in solvated diffusion and minor differences in the short-time mobility of BODIPY in SALI-n. This suggested that the observed decline of transport diffusivity in SALI-n mainly stemmed from the reduction in the pore size when these flexible chains are present. We anticipate that this proof of concept will assist in understanding how pore functionalization can physically and chemically affect mass transport in MOFs and will be useful in further guiding the design of PSM to realize the optimal performance of MOFs for various applications.
Consensus of multiagent systems with nonlinear dynamics and time‐varying communication delays

This paper deals with the local consensus of multiagent systems with nonlinear dynamics communication delays simultaneously. By introducing a weighted average state and applying the properties of the Laplacian matrix eigenvalues, the system is decoupled into several subsystems, firstly, to reduce complexity of theory analysis. Then, a new augmented vector containing single and double integral terms is constructed and the corresponding Lyapunov functional with triple integral terms is introduced. Meanwhile, in order to improve the estimating accuracy of the derivatives of constructed Lyapunov functional, single integral inequalities and double integral inequalities via auxiliary functions, an extended relaxed integral inequality and an reciprocally convex approach are used, as a result, stability criterion with less conservatism is derived, which guarantees the local consensus of the considered systems. Finally, numerical examples are provided to check the improvement of the proposed method over the existing works.
Different histories but similar genetic diversity and structure for black walnut in Indiana and Missouri

Missouri and Indiana have markedly different histories of glaciation and recolonization by forest trees. These states also differ in land use patterns and degree of anthropogenic landscape change such as forest fragmentation. To determine the overall effects of these and other demographic differences on the levels of genetic diversity and structure in black walnut (Juglans nigra L.) more than 550 total black walnut trees from nine populations in Indiana and 10 in Missouri were sampled and analyzed using 12 nuclear microsatellite loci.
Influences of landform as a confounding variable on SOM-NDVI association in semiarid Ordos Plateau

Soil organic matter (SOM) plays an important role in maintaining vegetation cover and thus mitigating land erosion of fragile terrestrial ecosystems such as in the Northern Ordos Plateau of China (NOPC). However, little information is available on whether and how SOM varies spatially as an intrinsic characteristic of landform in NOPC. The objective of this study was to examine the spatial associations of SOM with landform and vegetation cover. The study was conducted in a 23,000-km 2 area within NOPC because this area has landforms of mobile dunes (MD), flat dunes (FD), grassy sandy land (GSL), flat sandy bedrocks (FSB), and swamps and salt lakes (SW), which are typical landforms in semiarid ecosystems. SOM was determined using a standard laboratory analysis method for 5 cm topsoil samples collected at 72 locations across the study area. In addition, the 250 m Multitem- poral Moderate Resolution Imaging Spectroradiometer (MODIS) imageries taken in the period from August 2006 to August 2010 were used to extract Normalized Difference Vegetation Index (NDVI) which in turn was used as the surrogate of vegetation cover. Classic and geostatistical methods were used to compare SOM concentration across different landforms. The results indicated that an area with a greater value for NDVI (i.e. better vegetation cover) tended to have a higher SOM concentration regardless of the landform types. However, the association between SOM and NDVI varied from one landform to another. The SW and GSL had a highest SOM concentration, while MD had a lowest concentration. For the study area as a whole and the FD, GSL, and MD, SOM was found to be the sole function of NDVI, whereas, for the FSB, SOM was influenced by several intrinsic variables, namely ground surface altitude, slope, and aspect, as well as NDVI. SOM for the SW landform was found to be a function of NDVI. Furthermore, SOM and NDVI exhibited a consistent spatial pattern of increasing from north to south and from west to east. The highest SOM concentration of 3.5% occurred along an east-westward belt, which is adjacent to water pathways, in the mid part of the study area.
HETEROGENOUS ITERATED LEARNING 2

How does the process of information transmission affect the cultural or linguistic products that emerge? This question is often studied experimentally and computationally via iterated learning: a procedure in which participants learn from previous participants in a chain. Iterated learning is a powerful tool because, when all participants share the same priors, the stationary distributions of the iterated learning chains reveal those priors. In many situations, however, it is unreasonable to assume that all participants share the same prior beliefs. We present four simulation studies and one experiment demonstrating that when the population of learners is heterogeneous, the behavior of an iterated learning chain can be unpredictable, and is often systematically distorted by the learners with the most extreme biases. This results in group-level outcomes that reflect neither the behavior of any individuals within the population nor the overall population average. We discuss implications for the use of iterated learning as a methodological tool as well as for the processes that might have shaped cultural and linguistic evolution in the real world.
An updated C. elegans body muscle transcriptome for studies in muscle formation and function

The body muscle is an important tissue used in organisms for proper viability and 24 locomotion. The contractile unit of the muscle is the sarcomere, which is ultimately 25 responsible for the contraction reaction leading to movement. Although this tissue is 26 generally well studied and characterized, and many pathways have been elucidated 27 throughout the years, we still lack a comprehensive understanding of its transcriptome, 28 and how it controls muscle development and function. Here, we have updated a nuclear 29 FACS sorting-based approach to isolate and sequence a high-quality muscle 30 transcriptome from C. elegans mixed stage animals. We have identified 2,848 muscle-31 specific protein-coding genes, including 78 transcription factors and 206 protein-coding 32 genes containing an RNA binding domain. We studied their interaction network, 33 performed a detailed promoter analysis, and identified novel muscle-specific cis -acting 34 elements. We have also identified 16 high-quality muscle-specific miRNAs, studied their 35 function in vivo using fluorochrome-based analyses, and developed the first high-quality 36 miRNA Interactome in a living organism, incorporating other muscle-specific datasets 37 produced by our lab and others. 38 Our study expands our understanding of how muscle tissue functions in C. elegans and in turn, provide results that can in the future be applied to humans to study muscular-40 related diseases. 43
The Impact of Tax and Expenditure Policies on Income Distribution : Evidence from a Large Panel of Countries

The main focus of this paper is on the potential role that taxation and public expenditure policies play in general in affecting income distribution. We find that progressive personal income taxes and corporate income taxes reduce income inequality. The effect of corporate income taxes seems to be eroded away in open or globalized economies. We also generally find that general consumption taxes, excise taxes and customs duties have a negative impact on income distribution. On the expenditure side, we find that higher shares of GDP on social welfare, education, health and housing public expenditures have a positive impact on income distribution.
Can machine learning help forecasting fiscal crises in emerging and developing countries?*

Pre - existing public debt vulnerabilities have been exacerbated by the effects of the pandemic, raising the risk of fiscal crises especially in emerging and developing countries. This underscores the importance of models aimed at forecasting the occurrence of sovereign debt crises and capturing the main determinants of fiscal distress episodes. In this regard, our paper shows that machine learning techniques are able to outperform standard econometric approaches. The analysis also identifies the variables that are the most relevant predictors of fiscal crises and provides an assessment of their impact on the probability of observing a crisis episode.
An assessment of multidimensional wellbeing in rural Rwanda: impacts of and implications for rural development and natural resource conservation

This study applies a multidimensional definition of wellbeing, which includes material, social and subjective dimensions, to household level social research in rural Rwanda. Its contribution lies in applying the approach to three different fields: the study of cultural difference; natural resource management; and agrarian change, and in combining a wellbeing assessment with dominant theories or concepts in each. Rwanda has received acclaim for meeting development targets despite high levels of poverty and population density. However, due to centralised, target driven policy, those impacts are contested and this thesis presents rare empirical insights from the perspective of rural inhabitants themselves. The assessment of rural wellbeing forming the basis of three empirical papers reveals that many people struggle to meet basic needs for food, shelter and fuel. In contrast to development indicators, data reveal wellbeing to be falling among many rural households and inequality to be increasing, despite investment-driven health, education and security improvements. Far-reaching policies promoting rural and agricultural modernisation, alongside reconciliation between ethnic groups, appeared only to emphasize difference between groups, with outcomes of poverty reproduced for those with little relative power. The Twa, an indigenous people, suffer acute difficulties, exacerbated by reduced forest access. However application of a framework combining wellbeing and ecosystem services reveals that a landscape approach to natural resource management could realise synergies between local resource needs and conservation of biodiversity in Rwanda’s rich tropical forests. The pervasive and authoritarian nature by which development targets are pursued, for example enforcing rural villagisation, has resulted in a perceived loss of freedom, which inhibited local systems of knowledge, labour, trade and social interaction. While such consequences are commonly overlooked, more holistic approaches such as this enable interpretation of complex interrelated systems and promote awareness of local perspectives, with critical implications for the design and assessment of development policy.
Automated Processing of Colour Stereo Georeferenced Images for Road Inventory

Road inventory with a Mobile Mapping System (MMS) consists of two basic steps: data acqu1S1t1on and data post processing. The data, colour stereo georeferenced images, is captured by Colour Progressive Scan CCD cameras which are integrated and time tagged with GPS/INS. Collected information is analysed in a post-process in order to obtain information about roads and road signs. This paper presents an overview of the road inventory system (MMS) and describes in detail the data processing module for road inventory and automatic inventory of road signs from colour stereo georeferenced images. The inventory from georeferenced stereo images is performed in two basic alternatives: semiautomatic and automatic. The semiautomatic alternative is designed for task survey (a single point 3D measurements). This approach demands interaction between operator and software. In order to perform 3D measurement, a point has to be selected in one of the stereo images. The epipolar line is then calculated in the second image. The corresponding point is found along the line with template matching or by manual selection performed by an operator. The image point positioning is followed by a set of transformations, which convert 2D image co-ordinates into 3D global co-ordinates. An automatic alternative is designed for road signs inventory. This option employs step-wise processing: colour based object recognition and 3D positioning. The object recognition uses several image processing techniques: colour based segmentation, edge detection in colour space and automatic shape detection. Positioning is initiated by "Property Based Matching" and completed by image co-ordinate transformation into a global co-ordinate frame. The software was developed using object oriented Visual C++ language.
Off-policy Model-based Learning under Unknown Factored Dynamics

Off-policy learning in dynamic decision problems is essential for providing strong evidence that a new policy is better than the one in use. But how can we prove superiority without testing the new policy? To answer this question, we introduce the G-SCOPE algorithm that evaluates a new policy based on data generated by the existing policy. Our algorithm is both computationally and sample efficient because it greedily learns to exploit factored structure in the dynamics of the environment. We present a finite sample analysis of our approach and show through experiments that the algorithm scales well on high-dimensional problems with few samples.
Big data-based arti�cial intelligence for e�cient digital screen usage management among Chinese children and adolescents during the COVID-19 pandemic

This study investigated screen-time behaviors of Chinese children and adolescents and the e�cacy of arti�cial intelligence (AI)- based alerts in screen-time behavior correction. Data from 6,716 children and adolescents with AI-enhanced tablets that recorded behavioral and light environment data during use were analyzed. The mean daily screen time was 67.10 ± 48.26 min. The screen time of junior-high-school students exceeded 1.5 h (92.50 ± 75.06 min) and that of school-aged participants exceeded 4 h per week. Children younger than two years used tablets for more than 45 min per day. Learning accounted for more than 50% of participants’ screen time. The distance alarm was triggered 807,355 times. Some participants (31.03%, 2061/6643) used tablets for 1 h at an average distance < 50 cm. Over 70% of the participants used the tablet under an illuminance < 300 lx during the day and more than 60% under an illuminance < 100 lx at night. More than 85% of the participants’ ambient light exceeded 4,000 K color temperature at night. The screen time of school-aged participants was longer than that of preschool-aged children. The recorded illumination was insu�cient and was paired with a high color temperature at night. AI can effectively remind children and adolescents to correct unhealthy behaviors during screen time.
Reduced transpiration without changes in root water uptake patterns in degraded trees in semi-arid afforestation ecosystems

While reforestation in water-limited areas has increased vegetation coverage, an increasing number of studies have reported that large-scale plantations are suffering from tree degradation, which is characterized by short trees, small size, and dieback. Moreover, the changes in hydrological processes of degraded trees within the soil-plant system remain poorly 15 understood. Here, the stable isotope method ( 2 H, 18 O, and 13 C) and thermal dissipation technique were used to compare the soil water dynamics, tree transpiration, root water uptake patterns, and intrinsic water-use efficiency (WUE i ) of Populus simonii under different degradation degrees (no degradation, ND; light degradation, LD; or severe degradation, SD) in the 2021 growing season. As tree degradation intensified, the root weight density decreased significantly ( P <0.05) and the root proportion of the shallow layer (0–40 cm) increased. Influenced by precipitation recharge, the soil volumetric water content 20 (SWC) of the shallow layer did not show significant differences ( P >0.05) among the different degradation degrees. The SWC of the middle (40–80 cm) and deep (80–200 cm) layers were significantly ( P <0.05) lower in the ND plot than the LD
Variación geográfica en la morfología del esqueleto postcraneal de las poblaciones humanas de Pampa y Patagonia durante el Holoceno Tardío : una aproximación morfométrica

This book assesses the patterns of morphological variation in Late Holocene human populations of Pampa and Continental Patagonia in southern South America, using postcranial skeletons to discuss the evolutionary processes that shaped those patterns. It represents the first regionally and temporally delimited survey of postcranial variation during the Late Holocene in this part of South America. Spanish text.
Water vapor measurements inside clouds and storms using a differential absorption radar

Abstract. NASA's Vapor In-cloud Profiling Radar (VIPR) is a tunable G-band radar designed for in-cloud and precipitation humidity remote sensing. VIPR estimates humidity using the differential absorption radar (DAR) technique. This technique exploits the difference between atmospheric attenuation at different frequencies (“on” and “off” an absorption line) and combines it with the ranging capabilities of the radar to estimate the absorbing gas concentration along the radar path. We analyze the VIPR humidity measurements during two NASA field campaigns: (1) the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign, with the objective of studying wintertime snowstorms focusing on east coast cyclones; and (2) the Synergies Of Active optical and Active microwave Remote Sensing Experiment (SOA2RSE) campaign, which studied the synergy between DAR (VIPR) and differential absorption lidar (DIAL, the High altitude Lidar Observatory – HALO) measurements. We discuss a comparison with dropsondes launched during these campaigns as well as an intercomparison against the ERA5 reanalysis fields. Thus, this study serves as an additional evaluation of ERA5 lower tropospheric humidity fields. Overall, in-cloud and in-snowstorm comparisons suggest that ERA5 and VIPR agree within 20 % or better against the dropsondes. The exception is during SOA2RSE (i.e., in fair weather), where ERA5 exhibits up to a 50 % underestimation above 4 km. We also show a smooth transition in water vapor profiles between the in-cloud and clear-sky measurements obtained from VIPR and HALO respectively, which highlights the complementary nature of these two measurement techniques for future airborne and space-based missions.