Miracle-dz/UniFAR-FTUs huggingface dataset:
Effective Population Size and the Effects of Demography on Cultural Diversity and Technological Complexity

A central tenet of the so-called demographic hypothesis is that larger populations ought to be associated with more diverse and complex toolkits. Recent empirical tests of this expectation have yielded mixed results, leading some to question to what extent changes in population size might explain interesting changes in the prehistoric archaeological record. Here, I employ computer simulation as a heuristic tool to address whether these mixed results reflect deficiencies in the formal models borrowed from population genetics or problems with the generalizations archaeologists have derived from them. I show that two previously published and highly influential models highlight two different effects of demography. My results illustrate how natural selection and cultural selection weaken the relationship between census population size, cultural diversity, and mean skill level, suggesting that one should not expect population size to predict the diversity or complexity of a cultural trait under all conditions. The concept of effective population size is central to understanding why the effects of population size can vary among traits that are passed by different mechanisms of cultural transmission within the same population. In light of these findings, I suggest ways to strengthen (rather than abandon) empirical tests of the demographic hypothesis.
Unveiling Hidden Communities Through Cascading Detection on Network Structures

Community detection is the process of assigning nodes and links in significant communities (e.g. clusters, function modules) and its development has led to a better understanding of complex networks. When applied to sizable networks, we argue that most detection algorithms correctly identify prominent communities, but fail to do so across multiple scales. As a result, a significant fraction of the network is left uncharted. We show that this problem stems from larger or denser communities overshadowing smaller or sparser ones, and that this effect accounts for most of the undetected communities and unassigned links. We propose a generic cascading approach to community detection that circumvents the problem. Using real network datasets with two widely used community detection algorithms, we show how cascading detection allows for the detection of the missing communities and results in a significant drop of the fraction of unassigned links.
ParaMEME: a parallel implementation and a web interface for a DNA and protein motif discovery tool

Many advanced software tools fail to reach a wide audience because they require specialized hardware, installation expertise, or an abundance of CPU cycles. The worldwide web offers a new opportunity for distributing such systems. One such program, MEME, discovers repeated patterns, called motifs, in sets of DNA or protein sequences. This tool is now available to biologists over the worldwide web, using an asynchronous, single-program multiple-data version of the program called ParaMEME that runs on an Intel Paragon XP/S parallel computer at the San Diego Super-computer Center. ParaMEME scales gracefully to 64 nodes on the Paragon with efficiencies > 72% for large data sets. The worldwide web interface to ParaMEME accepts a set of sequences interactively from a user, submits the sequences to the Paragon for analysis, and e-mails the results back to the user. ParaMEME is available for free public use at http://@www.sdsc. edu/CompSci/Biomed/ MEME.
KBF1 (p50 NF-kappa B homodimer) acts as a repressor of H-2Kb gene expression in metastatic tumor cells

Downregulation of major histocompatibility complex class I expression is causally related to high malignancy and low immunogenicity of certain murine tumors. In this study, we have analyzed the roles of the nuclear factors KBF1/p50 and p65 in regulation of class I expression in high and low metastatic tumor cells. Low class I-expressing cells show at higher levels of KBF1/p50 and NF-kappa B (p50/p65) binding activity than high class I-expressing cells. However, an excess of KBF1 over NF- kappa B is observed in low expressing cells, while an excess of NF- kappa B over KBF1 is observed in high expressing cells. Stable transfection of a p65 expression vector into low class I-expressing cells activated H-2 transcription and cell surface expression, while stable transfection of p50 expression vector into high expressing cells suppressed H-2Kb transcription and cell surface expression. Our studies suggest that KBF1 has the potential of downregulating class I gene expression, whereas dimers containing the p65 subunit are activators of class I gene expression.
Exploiting dominant eigendirections for feedback compression for FDD-based massive MIMO systems

Acquiring reliable channel state information (CSI) at the basestation is crucial to fully exploit the advantages of massive multiple-input multiple-output (MIMO) systems. However, giving the basestation knowledge of the downlink channel is an important and challenging problem in frequency division duplexing (FDD) systems when the number of basestation antennas is large. In this paper, we propose an eigenvalue decomposition based feedback compression (EFC) framework that transforms the channel information for pursuing further reduction in feedback overhead. The main idea of EFC is to use the compressed channels for generating short-term CSI by exploiting the dominant eigendirections of long-term channel-statistical information. By using the proposed codebook, each user terminal sends the compressed channel information as short-term feedback and channel-statistical information as long-term feedback. Numerical results demonstrate that the proposed method achieves significant feedback overhead reduction over the conventional beamforming techniques under the same target sum rate requirement.
A new strategy for specific imaging of neural cells based on peptide-conjugated gold nanoclusters

Despite the significant progress in molecular imaging technologies that has been made in recent years, the specific detection of neural cells still remains challenging. Here, we suggest the use of gold nanoclusters (AuNCs) modified with a brain-targeting peptide as a potential imaging candidate for detecting neural cells in vitro and in mice. AuNCs of less than 10 nm (dynamic light scattering analysis) were first prepared using the “green” synthetic approach, and then a targeting peptide, rabies virus glycoprotein derived peptide (RDP), was conjugated to the AuNCs for improving the efficiency and specificity of neural cell penetration. The conjugate’s mechanism of cellular attachment and entry into neural cells was suggested to be receptor-mediated endocytosis through clathrin-coated pits. Also, noninvasive imaging analysis and animal studies indicated that the RDP-modified nanoclusters could concentrate in the brain and locate in neural cells. This study suggests the feasibility of using targeting peptide-modified nanoclusters for noninvasive imaging brain cells in vivo.
A Hybrid Approach for Mining Metabolomic Data

In this paper, we introduce a hybrid approach for analyzing metabolomic data about the so-called diabetes of type 2. The identi-cation of biomarkers which are witness of the disease is very important and can be guided by data mining methods. The data to be analyzed are massive and complex and are organized around a small set of individuals and a large set of variables (attributes). In this study, we based our experiments on a combination of ecient numerical supervised methods , namely Support Vector Machines (SVM), Random Forests (RF), and ANOVA, and a symbolic non supervised method, namely Formal Concept Analysis (FCA). The data mining strategy is based on ten spe-cic classication processes which are organized around three main operations , ltering, feature selection, and post-processing. The numerical methods are mainly used in ltering and feature selection while FCA is mainly used for visualization and interpretation purposes. The rst results are encouraging and show that the present strategy is well-adapted to the mining of such complex biological data and the identication of potential predictive biomarkers.
Lacustrine Fossil Preservation in Acidic Environments: Implications of Experimental and Field Studies for the Cretaceous–Paleogene Boundary Acid Rain Trauma

Abstract The effects of acidification on the preservation of buried lacustrine microfossils were evaluated using experimental tanks to simulate pH, depth, duration of acidification, and buffering conditions below the sediment/water interface of a hypothetical acidified lake. The taphonomic data provided from these experiments suggest that buffering by the host catchment (i.e., the CaCO3 content of the soils and outcrops that underlie the lake and drainage basin) is the primary factor promoting calcareous-fossil preservation under conditions of moderate and severe acidification. Global acid-rain fallout was a likely environmental consequence of the Chicxulub impact event at the Cretaceous– Paleogene boundary, and may have been important at other times in Earth history. Fossil preservation at the K/Pg boundary may have been affected by acidic groundwater leaching. Whereas the duration and intensity of the acid-rain fallout is poorly constrained, acid rain would have had varying effects on the acidity of lacustrine and fluvial environments with different acid-buffering capacities. Variations in acid-buffering capacities of lacustrine and fluvial catchments also may be a factor in the apparent extinction selectivity of non-marine aquatic fauna at the K/Pg boundary. Last appearances of taxa can result from poor preservation conditions or extinction—both of which may result from acidification. Last appearances observed at the species level, but not in higher taxa, may be the result of regional heterogeneities in catchment geology. Understanding local buffering conditions may be important for interpreting the continental fossil record at the K/Pg boundary.
Cerebrovascular reactivity measured by near-infrared spectroscopy.

BACKGROUND AND PURPOSE The pressure reactivity index (PRx) describes cerebral vessel reactivity by correlation of slow waves of intracranial pressure (ICP) and arterial blood pressure. In theory, slow changes in the relative total hemoglobin (rTHb) measured by near-infrared spectroscopy are caused by the same blood volume changes that cause slow waves of ICP. Our objective was to develop a new index of vascular reactivity, the hemoglobin volume index (HVx), which is a low-frequency correlation of arterial blood pressure and rTHb measured with near-infrared spectroscopy. METHODS Gradual hypotension was induced in piglets while cortical laser-Doppler flux was monitored. ICP was monitored, and rTHb was measured continuously using reflectance near-infrared spectroscopy. The HVx was recorded as a moving linear correlation between slow waves (20 to 300 seconds) of arterial blood pressure and rTHb. Autoregulation curves were constructed by averaging values of the PRx or HVx in 5-mm Hg bins of cerebral perfusion pressure. RESULTS The laser-Doppler flux-determined lower limit of autoregulation was 29.4+/-6.7 mm Hg (+/-SD). Coherence between rTHb and ICP was high at low frequencies. HVx was linearly correlated with PRx. The PRx and HVx both showed higher values below the lower limit of autoregulation and lower values above the lower limit of autoregulation. Areas under the receiver operator characteristic curves were 0.88 and 0.85 for the PRx and HVx, respectively. CONCLUSIONS Coherence between the rTHb and ICP waveforms at the frequency of slow waves suggests that slow waves of ICP are related to blood volume changes. The HVx has potential for further development as a noninvasive alternative to the PRx.
Recent advances in PBG structures

We propose a review of word science achievements in the extremely extended for the recent few years field of photonic band gap structures. The review concerns both theoretical and experimental investigations on PBG structures toward fabrication of the most optimal ones for different applications. The attention is given to the obtained results as well as to the used and developed methods.
Comparative API complexity analysis of two platforms for networked multiplayer games using a reference game

In this paper we propose the quantitative analysis of the complexity of a simple reference game implemented on a particular gaming platform as means for characterizing how the platform succeeds in easing the development of networked multiplayer games. We first present our own open source tool based on Sneed's Object-Point (OP) method for the automatic quantitative assessment of the complexity of a software API by analyzing a source code using the API. We then apply our tool, together with the recently released JSComplexity tool based on classical software complexity metrics, to compare two platforms for networked multiplayer games, the open source realXtend Tundra SDK and the proprietary Union. As the reference games we use existing implementations of the simple Pong game atop the two platforms. Our data shows that these complexity metrics reveal API design tradeoffs, resulting in complexity differences in the reference games.
Circuit Modeling and Performance Analysis of Multi-Walled Carbon Nanotube Interconnects

Metallic carbon nanotubes (CNTs) have received much attention for their unique characteristics as a possible alternative to Cu interconnects in future ICs. Until this date, while almost all fabrication efforts have been directed toward multiwalled CNT (MWCNT) interconnects, there is a lack of MWCNT modeling work. This paper presents, for the first time, a detailed investigation of MWCNT-based interconnect performance. A compact equivalent circuit model of MWCNTs is presented for the first time, and the performance of MWCNT interconnects is evaluated and compared against traditional Cu interconnects, as well as Single-Walled CNT (SWCNT)-based interconnects, at different interconnect levels (local, intermediate, and global) for future technology nodes. It is shown that at the intermediate and global levels, MWCNT interconnects can achieve smaller signal delay than that of Cu interconnects, and the improvements become more significant with technology scaling and increasing wire lengths. At 1000- global or 500- intermediate level interconnects, the delay of MWCNT interconnects can reach as low as 15% of Cu interconnect delay. It is also shown that in order for SWCNT bundles to outperform MWCNT interconnects, dense and high metallic-fraction SWCNT bundles are necessary. On the other hand, since MWCNTs are easier to fabricate with less concern about the chirality and density control, they can be attractive for immediate use as horizontal wires in VLSI, including local, intermediate, and global level interconnects.
Fibrin Hydrogel Based Bone Substitute Tethered with BMP-2 and BMP-2/7 Heterodimers

Current clinically used delivery methods for bone morphogenetic proteins (BMPs) are collagen based and require large concentrations that can lead to dangerous side effects. Fibrin hydrogels can serve as osteoinductive bone substitute materials in non-load bearing bone defects in combination with BMPs. Two strategies to even further optimize such a fibrin based system include employing more potent BMP heterodimers and engineering growth factors that can be covalently tethered to and slowly released from a fibrin matrix. Here we present an engineered BMP-2/BMP-7 heterodimer where an N-terminal transglutaminase substrate domain in the BMP-2 portion provides covalent attachment to fibrin together with a central plasmin substrate domain, a cleavage site for local release of the attached BMP-2/BMP-7 heterodimer under the influence of cell-activated plasmin. In vitro and in vivo results revealed that the engineered BMP-2/BMP-7 heterodimer induces significantly more alkaline phosphatase activity in pluripotent cells and bone formation in a rat calvarial model than the engineered BMP-2 homodimer. Therefore, the engineered BMP-2/BMP-7 heterodimer could be used to reduce the amount of BMP needed for clinical effect.
Phosphoproteomic characterization of DNA damage response in melanoma cells following MEK/PI3K dual inhibition

Significance Growing evidence suggests that successful intervention in many human cancers will require combinations of therapeutic agents. Critical to this effort will be a detailed understanding of the crosstalk between signaling networks that modulate proliferation, cell death, drug sensitivity, and acquired resistance. Here we investigated DNA-damage signaling elicited by small-molecule inhibitors against MAP/ERK kinase (MEK) and PI3K in melanoma cells. This work, performed using cutting-edge mass spectrometry proteomics, uncovered a burst of signaling among proteins in the DNA-damage pathway upon initiation of the cell-death program by agents targeting the RAS–RAF–MEK and PI3K–AKT–mTOR pathways. These signals may prove important to the short- and long-term sensitivity of tumor cells to MEK- and PI3K-targeted therapies. Targeted therapeutics that block signal transduction through the RAS–RAF–MEK and PI3K–AKT–mTOR pathways offer significant promise for the treatment of human malignancies. Dual inhibition of MAP/ERK kinase (MEK) and phosphatidylinositol 3-kinase (PI3K) with the potent and selective small-molecule inhibitors GDC-0973 and GDC-0941 has been shown to trigger tumor cell death in preclinical models. Here we have used phosphomotif antibodies and mass spectrometry (MS) to investigate the effects of MEK/PI3K dual inhibition during the period immediately preceding cell death. Upon treatment, melanoma cell lines responded by dramatically increasing phosphorylation on proteins containing a canonical DNA damage-response (DDR) motif, as defined by a phosphorylated serine or threonine residue adjacent to glutamine, [s/t]Q. In total, >2,000 [s/t]Q phosphorylation sites on >850 proteins were identified by LC-MS/MS, including an extensive network of DDR proteins. Linear mixed-effects modeling revealed 101 proteins in which [s/t]Q phosphorylation was altered significantly in response to GDC-0973/GDC-0941. Among the most dramatic changes, we observed rapid and sustained phosphorylation of sites within the ABCDE cluster of DNA-dependent protein kinase. Preincubation of cells with the inhibitors of the DDR kinases DNA-dependent protein kinase or ataxia-telangiectasia mutated enhanced GDC-0973/GDC-0941–mediated cell death. Network analysis revealed specific enrichment of proteins involved in RNA metabolism along with canonical DDR proteins and suggested a prominent role for this pathway in the response to MEK/PI3K dual inhibition.
Correcting GNSS NLOS by 3D LiDAR and Building Height

Occurrence of autonomous driving introduces high requirement in GNSS positioning performance. GNSS is currently the only source providing absolute positioning information. It is indispensable for initial position estimation for the high definition mapbased localization solution in autonomous driving. Satisfactory positioning accuracy can be obtained in open space or sub-urban areas. However, its performance is heavily challenged in super-urbanized scenarios with the positioning error going up to even 100 meters, due to the well-known NLOS receptions which dominates the GNSS positioning errors. The recent state-of-art rangebased 3D map aided GNSS (3DMA GNSS) can mitigate most of the NLOS receptions. However, ray-tracing simulation is timeconsuming. Therefore, we present a novel method to detect the NLOS caused by surrounding buildings and correct the pseudorange measurements using 3D point clouds and building height without ray-tracing simulation. To estimate the geometry and pose of the building relative to GNSS receiver, a surface segmentation method is employed to detect the surrounding building walls. NLOS errors are estimated by integrating the geometry, pose relative to the GNSS receiver and satellites information. Finally, position estimation of GNSS receiver is implemented by weighted least square (WLS) based on the corrected and healthy pseudorange measurements. Dynamic experiment is conducted to evaluate the errors caused by the NLOS receptions and to verify the effectiveness of the proposed method in a deep urbanized area, Hong Kong.
Development of comorbidity-adapted exercise protocols for patients with knee osteoarthritis

Background Exercise therapy is generally recommended for patients with osteoarthritis (OA) of the knee. Comorbidity, which is highly prevalent in OA, may interfere with exercise therapy. To date, there is no evidence-based protocol for the treatment of patients with knee OA and comorbidity. Special protocols adapted to the comorbidity may facilitate the application of exercise therapy in patients with knee OA and one or more comorbidities. Purpose The purpose of this study was to develop comorbidity-adapted exercise protocols for patients with knee OA and comorbidity. Method Several steps were undertaken to develop comorbidity-adapted protocols: selection of highly prevalent comorbidities in OA, a literature search to identify restrictions and contraindications for exercise therapy for the various comorbid diseases, consultation of experts on each comorbid disease, and field testing of the protocol in eleven patients with knee OA and comorbidity. Results Based on literature and expert opinion, comorbidity-adapted protocols were developed for highly prevalent comorbidities in OA. Field testing showed that the protocols provided guidance in clinical decision making in both the diagnostic and the treatment phase. Because of overlap, the number of exercise protocols could be reduced to three: one for physiological adaptations (coronary disease, heart failure, hypertension, diabetes type 2, chronic obstructive pulmonary diseases, obesity), one for behavioral adaptations (chronic a-specific pain, nonspecific low back pain, depression), and one for environmental adaptations (visual or hearing impairments). Evaluation of patient outcome after treatment showed significant (P<0.05) and clinically relevant improvements in activity limitations and pain. Conclusion Comorbidity-adapted exercise protocols for patients with knee OA were developed, providing guidance in clinical reasoning with regard to diagnostics and treatment. To evaluate the effectiveness of treatment in line with our protocols, a randomized clinical trial should be performed.
Phagocytosis imprints heterogeneity in tissue-resident macrophages

Tissue-resident macrophages display varying phenotypic and functional properties that are largely specified by their local environment. One of these functions, phagocytosis, mediates the natural disposal of billions of cells, but its mechanisms and consequences within living tissues are poorly defined. Using a parabiosis-based strategy, we identified and isolated macrophages from multiple tissues as they phagocytosed blood-borne cellular material. Phagocytosis was circadianally regulated and mediated by distinct repertoires of receptors, opsonins, and transcription factors in macrophages from each tissue. Although the tissue of residence defined the core signature of macrophages, phagocytosis imprinted a distinct antiinflammatory profile. Phagocytic macrophages expressed CD206, displayed blunted expression of Il1b, and supported tissue homeostasis. Thus, phagocytosis is a source of macrophage heterogeneity that acts together with tissue-derived factors to preserve homeostasis.