Miracle-dz/UniFAR-FTUs huggingface dataset:
Dental Paleobiology in a Juvenile Neanderthal (Combe-Grenal, Southwestern France)

Simple Summary Numerous prehistoric sites in Europe and the Near East provided bones and dental remains of the populations of the past. One of them is the Combe-Grenal Cave (SW France), where fossils of children and adults represent the Neanderthals who lived there more than 60 ky ago, during a harsh period of the last glaciation. In this paper, we analyze a sample of the tartar of a juvenile individual. The numerous bacteria forming the plaque are compared to those of one adult from Israel, Kebara 2, revealing the differences between the most common bacteria in a young and an older individual, probably because of their immunological systems, and the different living conditions of the human groups they represented. Abstract Combe-Grenal site (Southwest France) was excavated by F. Bordes between 1953 and 1965. He found several human remains in Mousterian levels 60, 39, 35 and especially 25, corresponding to MIS 4 (~75–70/60 ky BP) and with Quina Mousterian lithics. One of the fossils found in level 25 is Combe-Grenal IV, consisting of a fragment of the left corpus of a juvenile mandible. This fragment displays initial juvenile periodontitis, and the two preserved teeth (LLP4 and LLM1) show moderate attrition and dental calculus. The SEM tartar analysis demonstrates the presence of cocci and filamentous types of bacteria, the former being more prevalent. This result is quite different from those obtained for the two adult Neanderthals Kebara 2 and Subalyuk 1, where more filamentous bacteria appear, especially in the Subalyuk 1 sample from Central Europe. These findings agree with the available biomedical data on periodontitis and tartar development in extant individuals, despite the different environmental conditions and diets documented by numerous archeological, taphonomical and geological data available on Neanderthals and present-day populations. New metagenomic analyses are extending this information, and despite the inherent difficulties, they will open important perspectives in studying this ancient human pathology.
The impact of dialogic reflections on teacher autonomy

ABSTRACT Teacher autonomy refers to a teacher’s empowerment in the classroom, school, and community, leading to instructional efficacy and professionalism. Despite its proven contribution to pedagogical decision-making, studies reveal that many teachers lack sufficient autonomy mainly owing to institutional constraints. It is suggested that teachers embrace such restraints and become autonomous by initiating dialogic reflections with their colleagues and reaching contextualized decisions within a community of practice. So far, no study has explored how dialogic reflections can be performed among EFL (English as a Foreign Language) teachers. To fill the gap, the researcher investigated the process of dialogic reflections and explored whether it would affect the autonomy levels of Turkish EFL teachers. The data were collected through a teacher autonomy scale and by investigating the participants’ dialogic reflections. The results indicated that teacher autonomy levels increased thanks to social interdependence through collaborative decision-making.
Sensor enhanced microfluidic devices for cell based assays and organs on chip

Cell-based assays and organ-like substrates gather increasing attention due to their potentials in diagnostic and drug development. The use of these cell-based systems will allow to better understand in-vivo processes and to test for the direct influence of different substances on cell viability or metabolic activity e.g. in drug development and in addition to identify the influence of generated metabolites or different cell types. In this paper we present a respective technical platform, which enables the use of such cell-based assays. The platform is based on a microfluidic cell-assay toolbox, designed in a fashion allowing to minimize manual steps for cell culture on chip. Elements being essential for this work include membrane elements integrated into a microfluidic device for the separation of liquid stream together with a targeted supply of reagents and a three dimensional feeding of embedded cells. The influence of the metabolism from one cell type on the other can be evaluated due to the arrangement of cell compartments as interacting networks. A respective Lab-on-a-chip handling platform allows for the direct manipulation on a microscope stage and an incubator-free cell culture. Furthermore, luminescent sensors represent promising tools to be embedded into the microfluidic system to monitor the on-chip conditions or to provide information on cell viability and metabolic activity. Finally, examples for implemented assays on chip will be presented, ranging from cell culture showing the cell behavior in respect to surface functionalization and different growth conditions to finally embedding organ-on-chip structures of cultured cell lines.
The flow between counter-rotating disks at high Reynolds number

We investigate the von Karman similarity equations for fluid flow between two infinite coaxial disks that rotate with equal rotation rates and in opposite directions. The nonlinear singular perturbation problem for high Reynolds number is analyzed by formal asymptotic methods. We construct an asymptotic solution valid away from the boundary layers that occur on each disk. This solution requires that the fluid away from the boundary layers is essentially nonrotating, and thus confirms a conjecture of Stewartson. Moreover, its properties agree precisely with estimates for a solution whose existence has been proven by McLeod and Parter.
Using training to improve drivers’ knowledge and understanding of advanced driver assistance systems—an experimental study

Use of Advanced Driver Assistance Systems (ADAS) has increased exponentially in the past decade. However, ADAS features are complex, and drivers must understand the limitations and conditions in which ADAS should be used. ADAS today is not capable of taking over driving indefinitely and should only be used as a support system (SAE 2021). Drivers need to monitor their surroundings and be ready to take control of the car whenever necessary. Previous studies show drivers using multiple methods to understand ADAS. Owner’s Manual is the preferred method (McDonald et al. 2016); however, it is lengthy and not user-friendly (Mehlenbacher et al. 2002). Providing compact and essential training can help drivers understand when and how to use ADAS and help calibrate trust (Beggiato and Krems 2013). To examine improvement in drivers’ understanding and use of ADAS, we evaluated impact of three methods using a randomized controlled experiment in an advanced driving simulator. We measured knowledge of Adaptive Cruise Control (ACC) via surveys, verbal probes, and instructions while experiencing ACC in a driving simulator.
The Prospect of Application and Future Development of Library Information Technology in the Era of Big Data

: Big data technology plays an important role in information collection, collation, analysis and refining. It also plays an important role in the application of information technology in university library. This paper uses big data technology to mine the behavior of hidden readers in structured and semi-structured data information, and find the needs of hidden readers, so as to improve the optimal allocation of library services, resources and readers' needs. The results show that the maximum consultation times of Library B is 6425, and the minimum consultation times of library A is 5316
Analysis of the evolution of temporal and spatial characteristics of inbound tourism flow since the western development drive

: Based on the relevant data of inbound tourism of China and various provinces from 2000 to 2019, using the network density, centrality, structure hole and other indicators to study the evolution principle of inbound tourism in western China. Especially, the study was carried out from the perspective of macro and medium, and enrich the research results. According to the research results, the development pace of inbound tourism in western China had maintained a high rate and exceeded domestic average level in 2008; Shaanxi Province plays a vital role in western region. It is the destination and transfer station of inbound tourism. It also plays an important role as a hub in the development of inbound tourism in the entire northwest region, and promotes the development of entire region.
Chinese Character Components Segmentation Method Based on Faster RCNN

To solve the component segmentation problem caused by the sticking and overlapping of parts in incoherent handwritten calligraphy characters, we propose a Chinese character part segmentation method based on Faster RCNN. The method utilizes the advantages of Faster RCNN on multi-scale and small targets to solve difficult problems in component segmentation. The hierarchical features of the components were used in our proposed method to identify each layer of the Chinese character structure to obtain the components. Qualitative and quantitative calculations were used to test the segmentation effect of the proposed method. The experimental results demonstrate the accurate segmentation effectiveness of our method for adhering and overlapping components. In addition, these components could be retrieved accurately in the retrieval system, and the mean Average Precision of the top 30 retrieval results reached 95.7%. A better retrieval accuracy reflects a better segmentation effect from the side, which proves the effectiveness of the proposed method.
Rethinking DRAM's Page Mode With STT-MRAM

Spin torque magnetic random access memory (STT-MRAM) is a promising candidate for drop-in replacement for DRAM-based main memory because of its higher energy efficiency and similar latency to dynamic random access memory (DRAM). However, simply replacing DRAM with STT-MRAM without optimizations severely limits STT-MRAM from exploiting its full potential. STT-MRAM employs costly sense amplifiers that demand an order of magnitude more area and power than DRAM. To manage the high cost, STT-MRAM shares one sense amplifier across multiple bit-lines, exploiting the non-destructive nature of its read operation. This sense amplifier sharing reduces the size of row buffers; as a result, it incurs higher activation energy and lower performance. Other issues arise if STT-MRAM is required to be compatible with DRAM interfaces and policies. To address these challenges in a cost-effective manner, we propose STT-MRAM ARchiTecture supporting smart activation and sensing (SMART) that, unlike DRAM and conventional STT-MRAM, waits to do bit-line sensing until after receiving a column access command instead of a row activation command. This results in several benefits: larger pages, fewer sense amplifiers, lower activation power, higher bank-level parallelism, shorter latency, fewer address pins, and more efficient repairing of defective columns than conventional STT-MRAM. Our evaluation shows that SMART consumes lower energy while providing higher performance than conventional STT-MRAM and DRAM. Additionally, SMART consumes less area compared to conventional STT-MRAM.
Use of Clopidogrel in Ischemic Stroke Patients

Stroke is a clinical condition that develops rapidly and is caused by focal (diffused) brain injuries or damage accompanied by symptoms that can occur for 24 hours, and it can lead to death. Clopidogrel is an antiplatelet drug used to prevent stroke by reducing the ability of blood to clot. This study aimed to examine the usage pattern of clopidogrel in ischemic stroke patients at Sidoarjo Public Hospital during the period of January – December 2020. This study was observational and retrospective. The data were analyzed descriptively. Monotherapy of clopidogrel was registered in all patients (100%) with a dosage of 1 x 75 mg delivered orally. The use of clopidogrel with other antiplatelet drugs was 1 x 80 mg ASA delivered orally and 1 x 75 mg clopidogrel given orally for 1 patient. Keywords: clopidogrel, antiplatelet, ischemic stroke
On the validity of the flow rule postulate for geomaterials

This paper is concerned with a fundamental assumption in the theory of plasticity: the direction of plastic strain increments is independent of the loading (stress) increment direction. This assumption, also known as plastic flow rule postulate, works quite well for metal‐like materials. However, geomaterials such as sand present deformational mechanisms that are distinctive from those of metals when they are loaded. As such, we hereby examine the validity of this postulate for granular media accounting for their discrete nature. This is accomplished by analysing the mechanical behaviour of a cubic assembly of polydispersed spherical articles using a particle flow code. An extension to Gudehus' response envelope to three‐dimensional conditions is used to study the incremental character and influence of loading direction on the behaviour of these materials. It is found that plastic flow in granular media is governed by both current state variables and incremental loading direction and magnitude, especially under non‐axisymmetric stress conditions. The flow rule postulate of plasticity remains valid only in axisymmetric and biaxial conditions. We also verified that the plastic response might be significantly influenced by the stress path (or history) taken prior to loading. These findings raise the question of whether or not classic elastoplastic models based on the above postulate will have serious shortcomings, especially in true‐triaxial conditions. Copyright © 2013 John Wiley & Sons, Ltd.
Utility–Privacy Trade-Off in Distributed Machine Learning Systems

In distributed machine learning (DML), though clients’ data are not directly transmitted to the server for model training, attackers can obtain the sensitive information of clients by analyzing the local gradient parameters uploaded by clients. For this case, we use the differential privacy (DP) mechanism to protect the clients’ local parameters. In this paper, from an information-theoretic point of view, we study the utility–privacy trade-off in DML with the help of the DP mechanism. Specifically, three cases including independent clients’ local parameters with independent DP noise, dependent clients’ local parameters with independent/dependent DP noise are considered. Mutual information and conditional mutual information are used to characterize utility and privacy, respectively. First, we show the relationship between utility and privacy for the three cases. Then, we show the optimal noise variance that achieves the maximal utility under a certain level of privacy. Finally, the results of this paper are further illustrated by numerical results.
U-Net Based Segmentation and Characterization of Gliomas

Simple Summary Gliomas comprise 80% of all malignant brain tumors. We aimed to develop a deep learning-based framework for the automatic segmentation and characterization of gliomas. In this retrospective study, patients were included if they: (1) had a diagnosis of glioma confirmed by histopathology and (2) had preoperative MRI with the inclusion of FLAIR imaging. The deep learning-based U-Net framework was developed based on manual segmentation on FLAIR as the ground truth mask for automatic segmentation and feature extraction, which were used for the prediction of biomarker status and prognosis. A total of 208 patients were included from our internal dataset with stratified sampling to split the database into training and validation. An external dataset (n = 31) from an outside institution was used for testing. The dice similarity coefficient of the generated mask was 0.93 on the testing dataset. The prediction of the radiomic model achieved an AUC of 0.88 for IDH-1 and 0.62 for MGMT on the testing dataset. Our deep learning-based framework can detect and segment gliomas with excellent performance for the prediction of IDH-1 biomarker status and survival. Abstract (1) Background: Gliomas are the most common primary brain neoplasms accounting for roughly 40–50% of all malignant primary central nervous system tumors. We aim to develop a deep learning-based framework for automated segmentation and prediction of biomarkers and prognosis in patients with gliomas. (2) Methods: In this retrospective two center study, patients were included if they (1) had a diagnosis of glioma with known surgical histopathology and (2) had preoperative MRI with FLAIR sequence. The entire tumor volume including FLAIR hyperintense infiltrative component and necrotic and cystic components was segmented. Deep learning-based U-Net framework was developed based on symmetric architecture from the 512 × 512 segmented maps from FLAIR as the ground truth mask. (3) Results: The final cohort consisted of 208 patients with mean ± standard deviation of age (years) of 56 ± 15 with M/F of 130/78. DSC of the generated mask was 0.93. Prediction for IDH-1 and MGMT status had a performance of AUC 0.88 and 0.62, respectively. Survival prediction of <18 months demonstrated AUC of 0.75. (4) Conclusions: Our deep learning-based framework can detect and segment gliomas with excellent performance for the prediction of IDH-1 biomarker status and survival.
Bioactive Compounds from Marine Sponges and Algae: Effects on Cancer Cell Metabolome and Chemical Structures

Metabolomics represent the set of small organic molecules generally called metabolites, which are located within cells, tissues or organisms. This new “omic” technology, together with other similar technologies (genomics, transcriptomics and proteomics) is becoming a widely used tool in cancer research, aiming at the understanding of global biology systems in their physiologic or altered conditions. Cancer is among the most alarming human diseases and it causes a considerable number of deaths each year. Cancer research is one of the most important fields in life sciences. In fact, several scientific advances have been made in recent years, aiming to illuminate the metabolism of cancer cells, which is different from that of healthy cells, as suggested by Otto Warburg in the 1950s. Studies on sponges and algae revealed that these organisms are the main sources of the marine bioactive compounds involved in drug discovery for cancer treatment and prevention. In this review, we analyzed these two promising groups of marine organisms to focus on new metabolomics approaches for the study of metabolic changes in cancer cell lines treated with chemical extracts from sponges and algae, and for the classification of the chemical structures of bioactive compounds that may potentially prove useful for specific biotechnological applications.
Quantum Theory and Conceptuality: Matter, Stories, Semantics and Space-Time

We elaborate the new interpretation of quantum theory that we recently proposed, according to which quantum particles are considered conceptual entities mediating between pieces of ordinary matter which are considered to act as memory structures for them. Our aim is to identify what is the equivalent for the human cognitive realm of what physical space-time is for the realm of quantum particles and ordinary matter. For this purpose, we identify the notion of 'story' as the equivalent within the human cognitive realm of what ordinary matter is in the physical quantum realm, and analyze the role played by the logical connectives of disjunction and conjunction with respect to the notion of locality. Similarly to what we have done in earlier investigations on this new quantum interpretation, we use the specific cognitive environment of the World-Wide Web to elucidate the comparisons we make between the human cognitive realm and the physical quantum realm.
Entire Holomorphic Mappings in One and Several Complex Variables.

The present monograph grew out of the fifth set of Hermann Weyl Lectures, given by Professor Griffiths at the Institute for Advanced Study, Princeton, in fall 1974. In Chapter 1 the author discusses Emile Borel's proof and the classical Jensen theorem, order of growth of entire analytic sets, order functions for entire holomorphic mappings, classical indicators of orders of growth, and entire functions and varieties of finite order. Chapter 2 is devoted to the appearance of curvature, and Chapter 3 considers the defect relations. The author considers the lemma on the logarithmic derivative, R. Nevanlinna's proof of the defect relation, and refinements of the classical case.
Aroids Propagation by Tissue Culture: I. Shoot Tip Culture and Propagation of Xanthosoma violaceum

The Araceae, which comprises 115 genera and more than 2000 species, is widely distributed in all tropical and subtropical regions of the world (2). Vietnam is represented by 26 genera and about 60 species (3). Despite the promise of taro and other aroids as a future food source, the Araceae remain an under-exploited plant family. Several workers have shown that in vitro selection of salt-tolerant plants in general (1), and aroids in particular (7), is possible. This report describes a method for shoot tip micropropagation of Xanthosoma violaceum (blue taro).
CALCULATION OF NON-LIFTING POTENTIAL FLOW ABOUT ARBITRARY THREE-DIMENSIONAL BODIES

Abstract : A method is described for calculating, with the aid of an electronic computer, the incompressible potential flow about arbitrary, non-lifting, three- dimensional bodies. The method utilizes a source density distribution on the surface of the body and solves for the distribution necessary to make the normal velocity zero on the boundary. Plane quadrilateral surface elements are used to approximate the body surface, and the integral equation for the surface source density is replaced by a set of linear algebraic equations for the values of the source density on each of the quadrilateral elements. After this set of equations has been solved, which is accomplished by a Seidel iterative procedure, the flow velocities at points both on and off the body surface are calculated. This approach is completely general. Bodies are not required to be slender, analytically defined, or simply connected.
A Survey on Visual Simultaneously Localization and Mapping

Visual simultaneous localization and mapping (VSLAM) is an important branch of intelligent robot technology, which refers to the use of cameras as the only external sensors to achieve self-localization in unfamiliar environments while creating environmental maps. The map constructed by slam is the basis for subsequent robots to achieve autonomous positioning, path planning and obstacle avoidance tasks. This paper introduces the development of visual Slam at home and abroad, the basic methods of visual slam, and the key problems in visual slam, and discusses the main development trends and research hotspots of visual slam.