Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Landscape Disturbance on Animal Communities in Lake Tanganyika, East Africa

Abstract: Watershed deforestation, road building, and other anthropogenic activities result in sediment inundation of lacustrine habitats. In Lake Tanganyika, this threatens the survival of many rock‐dwelling species by altering the structure and quality of rocky habitats. We investigated the relationship between habitat quality, as related to watershed disturbance intensity, and the biodiversity of faunal communities at three rocky littoral sites of low, moderate, and high disturbance. Turbidity measurements and other environmental observations confirmed that our lake sites represented a gradient of disturbance conditions. We documented differences in species density (number of species per constant area or time), species richness, abundance, and trophic ecology for fishes, molluscs, and ostracods. Fish censuses were performed by scuba divers at 1–20 m and by remotely operated vehicle (ROV) at 40–80 m. In the fish surveys, abundance, species density and richness, and herbivory reached their maxima at intermediate water depths. The depth range of herbivores, however, was restricted at higher‐disturbance sites. The ROV fish surveys at the high‐disturbance site showed high species richness despite low species density and abundance, and piscivores were proportionally more prevalent than in all other surveys. Molluscs censused by diver quadrats and sieve samples showed decreasing species richness and species density (sieve samples only) with increasing disturbance and no significant abundance trend. Ostracod species richness was similar between low‐ and moderate‐disturbance sites but was markedly lower at the high‐disturbance site (species density and abundance data were not available). Our faunal analyses suggest that all three taxonomic groups are negatively affected by sediment inundation but may have varying response thresholds to disturbance. Further, this study emphasized the utility of using complementary survey techniques to monitor and ultimately manage biodiversity in complex freshwater ecosystems.
The Influence of Mother's Marital History on the Mother-Daughter Relationship in Black and White Households.

The central question addressed in the paper is whether teenage daughters are more or less likely to take on quasi-adult companionate and confederate roles vis-a-vis their mothers in maritally nonintact as compared to maritally intact homes. This question was investigated using sample survey data from a study of 449 black and white mothers and their teenaged daughters in Detroit, Michigan. Ten different measures of maternal marital history and current marital status, including measures of the presence and participation of father figures in the home, were developed. Criterion measures included single items and composite indexes for three domains of domestic behavior: the socio-emotional relationship between mother and daughter, task sharing, and parenting. Few significant differences were found by marital history for either black or white families.
Upregulated microRNA‐193a‐3p is responsible for cisplatin resistance in CD44(+) gastric cancer cells

Cisplatin is a well‐known anticancer drug used to treat various cancers. However, development of cisplatin resistance has hindered the efficiency of this drug in cancer treatment. Development of chemoresistance is known to involve many signaling pathways. Recent attention has focused on microRNAs (miRNAs) as potentially important upstream regulators in the development of chemoresistance. CD44 is one of the gastric cancer stem cell markers and plays a role in regulating self‐renewal, tumor initiation, metastasis and chemoresistance. The purpose of the present study was to examine the mechanism of miRNA‐mediated chemoresistance to cisplatin in CD44‐positive gastric cancer stem cells. We sorted gastric cancer cells according to level of CD44 expression by FACS and analyzed their miRNA expression profiles by microarray analysis. We found that miR‐193a‐3p was significantly upregulated in CD44(+) cells compared with CD44(−) cells. Moreover, SRSF2 of miR‐193a‐3p target gene was downregulated in CD44(+) cells. We studied the modulation of Bcl‐X and caspase 9 mRNA splicing by SRSF2 and found that more pro‐apoptotic variants of these genes were generated. We also found that downstream anti‐apoptotic genes such as Bcl‐2 were upregulated, whereas pro‐apoptotic genes such as Bax and cytochrome C were downregulated in CD44(+) cells compared to CD44(−) cells. In addition, we found that an elevated level of miR‐193a‐3p triggered the development of cisplatin resistance in CD44(+) cells. Inhibition of miR‐193a‐3p in CD44(+) cells increased SRSF2 expression and also altered the levels of multiple apoptotic genes. Furthermore, inhibition of miR‐193a‐3p reduced cell viability and increased the number of apoptotic cells. Therefore, miR‐193a‐3p may be implicated in the development of cisplatin resistance through regulation of the mitochondrial apoptosis pathway. miR‐193a‐3p could be a promising target for cancer therapy in cisplatin‐resistant gastric cancer.
Self-Formation of RPE Spheroids Facilitates Enrichment and Expansion of hiPSC-Derived RPE Generated on Retinal Organoid Induction Platform.

Purpose Retinal pigment epithelium (RPE) and neural retina could be generated concurrently through retinal organoid induction approaches using human induced pluripotent stem cells (hiPSCs), providing valuable sources for cell therapy of retinal degenerations. This study aims to enrich and expand hiPSC-RPE acquired with this platform and explore characteristics of serially passaged RPE cells. Methods RPE has been differentiated from hiPSCs with a published retinal organoid induction method. After detachment of neural retina on the 4th week, the remaining mixture was scraped from the dish and subjected to suspension culture for the formation of RPE spheroids. RPE sheets were isolated and digested for expansion. The cellular, molecular, and functional features of expanded RPE cells were evaluated by different assays. Results Under suspension culture, hiPSC-RPE spheroids with pigmentation self-formed were readily enriched by removing the non-retinal tissues. RPE sheets were further dissected and purified from the spheroids. The individualized RPE cells could be passaged every week for at least 5 times in serum medium, yielding large numbers of cells with high quality in a short period. In addition, when switched to a serum-free medium, the passaged RPE cells could mature in cellular, molecular, and physiological levels, including repigmentation, markers expression, and phagocytosis. Conclusions We developed a simple and novel RPE spheroids formation approach to enrich and expand hiPSC-RPE cells generated along with retinal neurons on a universal retinal organoid induction platform. This achievement will reduce the cost and time in producing retinal cells for basic and translational researches, in particular for retinal cell therapy.
Secrecy Capacity of a Class of Erasure Wiretap Channels in WBAN

In wireless body area networks (WBANs), the secrecy of personal health information is vulnerable to attacks due to the openness of wireless communication. In this paper, we study the security problem of WBANs, where there exists an attacker or eavesdropper who is able to observe data from part of sensors. The legitimate communication within the WBAN is modeled as a discrete memoryless channel (DMC) by establishing the secrecy capacity of a class of finite state Markov erasure wiretap channels. Meanwhile, the tapping of the eavesdropper is modeled as a finite-state Markov erasure channel (FSMEC). A pair of encoder and decoder are devised to make the eavesdropper have no knowledge of the source message, and enable the receiver to recover the source message with a small decoding error. It is proved that the secrecy capacity can be achieved by migrating the coding scheme for wiretap channel II with the noisy main channel. This method provides a new idea solving the secure problem of the internet of things (IoT).
ADHD and communication disorders

ADHD and communication disorders are both common neurodevelopmental disorders that often co-occur. Comorbidity (i.e. co-occurrence or two or more disorders in a person) is potentially important for the theory, the underlying aetiology, treatment, and prevention of the disorders. This chapter first reviews the extent of co-occurrence between ADHD and various subtypes of communication disorders (language disorders, speech sound disorders, social pragmatic communication disorders), along with their clinical manifestation. Next, the extant evidence to support or refute various models of comorbidity (i.e. artifactual versus non-artifactual) is reviewed and critiqued. The chapter concludes with a discussion of the implications of co-occurring communication disorders and ADHD for the clinical assessment and management of ADHD.
Localization Reliability Improvement Using Deep Gaussian Process Regression Model

With the widespread use of the Global Positioning System, indoor positioning technology has attracted increasing attention. Many systems with distinct deployment costs and positioning accuracies have been developed over the past decade for indoor positioning. The method that is based on received signal strength (RSS) is the most widely used. However, manually measuring RSS signal values to build a fingerprint database is costly and time-consuming, and it is impractical in a dynamic environment with a large positioning area. In this study, we propose an indoor positioning system that is based on the deep Gaussian process regression (DGPR) model. This model is a nonparametric model and it only needs to measure part of the reference points, thus reducing the time and cost required for data collection. The model converts the RSS values into four types of characterizing values as input data and then predicts the position coordinates using DGPR. Finally, after reinforcement learning, the position coordinates are optimized. The authors conducted several experiments on a simulated environment by MATLAB and physical environments at Tianjin University. The experiments examined different environments, different kernels, and positioning accuracy. The results showed that the proposed method could not only retain the positioning accuracy, but also save the computation time that is required for location estimation.
Eliciting Knowledge Bases with Defeasible Reasoning: A Comparative Analysis with Machine Learning

Faculty Name DIT School of Computing MSc in Computing (Advanced Software Development) Eliciting Knowledge Bases with Defeasible Reasoning: A Comparative Analysis with Machine Learning by Peter KEOGH This thesis compares the ability of an implementation of Defeasible Reasoning (via Argumentation Theory) to model a construct (mental workload) with Machine Learning. In order to perform this comparison a defeasible reasoning system was designed and implemented in software. This software was used to elicit a knowledge base from an expert in an experiment which was then compared with machine learning. The central findings of this thesis were that the knowledge based approach was better at predicting an objective performance measure, time, than machine learning. However, machine learning was better equiped to identify another object measure task membership. The knowledge base of the expert had a high concurrent validity with objective performance measures and a high convergent validity with existing measures of mental workload.
Default hierarchy formation and memory exploitation in learning classifier systems

Automated adaptation in a general setting remains a difficult and poorly understood problem. Reinforcement learning control problems model environments where an automated system must optimize a reinforcement signal by providing inputs to a black-box whose internal structure is initially unknown and persistently uncertain. Learning classifier systems (LCSs) are a class of rule-based systems for reinforcement learning control that use genetic algorithms (GAs) for rule discovery. Genetic algorithms are a class of computerized search procedures whose mechanics are based on natural genetics. This study examines two characteristic aspects of LCSs: default hierarchy formation and memory exploitation. Default hierarchies are sets of rules where the utilities of partially correct, but broadly applicable rules (defaults) are augmented by additional rules (exceptions). By forming default hierarchies, an LCS can store knowledge in parsimonious rule sets that can be incrementally refined. To do this, an LCS must have conflict resolution mechanisms that cause exceptions to consistently override defaults. This study examines typical LCS conflict resolution mechanisms and shows that they are inadequate in many situations. A new conflict resolution strategy called the priority tuning scheme is introduced. Experimentation shows that this scheme properly organizes default hierarchies in situations where traditional schemes fail. Analysis reveals that this technique greatly enlarges the class of exploitable default hierarchies. LCSs have the potential to adaptively exploit memory and extend their capabilities beyond simple stimulus-response behavior. This study develops a class of problems that isolate memory exploitation from other aspects of LCS behavior. Experiments show that an LCS can form rule sets that exploit memory. However, the LCS does not form optimal rule sets because of a limitation in its allocation of credit scheme. This study demonstrates this limitation and suggests an alternate scheme that automatically evolves multi-rule corporations as a remedy. Preliminary analysis illustrates the potential of this method. LCSs are a promising approach to reinforcement learning. This study has suggested several directions for refinement and improved understanding of LCSs. Further development of learning systems like LCSs should extend the applicability of automatic systems to tasks that currently require human intervention.
El receptor de la hormona de crecimiento humana (hGH) y la proteína de transporte de alta afinidad de la hGH

La hormona de crecimiento humana (hGH) circula parcialmente unida a su proteina de transporte de alta afinidad (GHBP) la cual resulta del clivaje proteolitico del dominio extracelular del receptor de GH. Recientemente la enzima TACE se identifico como la metaloproteasa responsable del clivaje y liberacion de GHBP a circulacion. Aunque aun se desconoce la funcion especifica de esta proteina de transporte, distintos trabajos en la literatura demuestran efectos que potencian y efectos inhibitorios sobre la accion de GH. Por otro lado, existen evidencias que demuestran una fuerte relacion entre la GHBP y el nivel de receptor de GH en el higado en situaciones fisiologicas y patologicas. Esto permitio proponer a la determinacion de GHBP en suero como un marcador periferico de la abundancia del receptor de GH en los tejidos. La determinacion de la concentracion de GHBP seria de especial interes para evaluar pacientes con diagnostico probable de insensibilidad a la accion de GH y orientar el posterior estudio de anormalidades en el gen del receptor de GH. En la presente revision, tambien se abordan dificultades metodologicas relacionadas a la medicion de GHBP serica. Human circulating growth hormone (GH) is partly bound to a high-affinity binding protein (GHBP) which is derived from proteolytical cleavage of the extracellular domain of the GH receptor. Recently, the metalloproteinase TACE has been identified as an important enzyme responsive for inducing GHBP shedding. Although the specific function of GHBP is not fully known, both enhancing and inhibitory roles of this binding protein on GH action have been proposed. Many reports have demonstrated a close relationship between GHBP and the liver GH receptor status in physiological conditions and diseases. Moreover, serum GHBP measurement has been proposed as an useful peripheral index of the GH receptor abundance. Related to the latter, circulating GHBP concentration would be of special interest for the evaluation of GH insensitivity due to GH receptor gene abnormalities. In addition, the present review also focus on methodological problems concerning serum GHBP measurement.
ROSAT HRI Observations of M31 Supernova Remnants

We have observed M31 using the ROSAT HRI. We have searched for X-ray emission from supernova remnants (SNRs) previously identified from surveys using narrowband optical observations. We find that a surprisingly small number of the identified SNRs are detected in X-rays at a threshold of ≈ 1035 ergs s-1. The absence of detected X-ray flux from many of the optically identified SNRs suggests that the local ISM density in the vicinity of these SNRs is typically quite low, less than 0.1 cm-3. The few that have been detected likely represent the upper end of the density distribution, having implied ambient densities in the range 0.1 to >10 cm-3. Since H I observations show that all SNRs are in regions with large column densities, which implies densities of 1-10 cm-3, a multicomponent ISM must be invoked. Our measured densities are upper limits for the dominant low-density component of the ISM.
The male gamete membrane protein DMP9/DAU2 is required for double fertilization in flowering plants

ABSTRACT All flowering plants exhibit a unique type of sexual reproduction called ‘double fertilization’ in which each pollen tube-delivered sperm cell fuses with an egg and a central cell. Proteins that localize to the plasma membrane of gametes regulate one-to-one gamete pairing and fusion between male and female gametes for successful double fertilization. Here, we have identified a membrane protein from Lilium longiflorum generative cells using proteomic analysis and have found that the protein is an ortholog of Arabidopsis DUF679 DOMAIN MEMBRANE PROTEIN 9 (DMP9)/DUO1-ACTIVATED UNKNOWN 2 (DAU2). The flowering plant DMP9 proteins analyzed in this study were predicted to have four transmembrane domains and be specifically expressed in both generative and sperm cells. Knockdown of DMP9 resulted in aborted seeds due to single fertilization of the central cell. Detailed imaging of DMP9-knockdown sperm cells during in vivo and semi-in vitro double fertilization revealed that DMP9 is involved in gamete interaction that leads to correct double fertilization. Summary: DMP9/DAU2 resident to the sperm cell surface arranges interactions with the egg cell that lead to the success of double fertilization.
Parsing statistical machine translation output

Despite increasing research into the use of syntax during statistical machine translation, the incorporation of syntax into language models has seen limited success. We present a study of the discriminative abilities of generative syntax-based language models, over and above standard n-gram models, with a focus on potential applications for Statistical Machine Translation (SMT). We show that in fact parsers are better able to discriminate between good and bad English, and that parsers, as well as n-gram language models, assign higher average log probabilities to references in comparison to SMT output.
Feature Selection for 2D and 3D Face Recognition

Face recognition is a popular research topic with a number of applications in several industrial sectors including security, surveillance, entertainment, virtual reality, and human–machine interaction. Both 2D images and 3D data can now be easily acquired and used for face recognition. For any 2D/3D face recognition system, feature extraction and selection play a significant role. Currently, both holistic and local features have been intensively investigated in the literature. In this article, fundamental background knowledge of face recognition, including 2D/3D data acquisition, data preprocessing, feature extraction, classification, and performance evaluation, is presented. The state-of-the-art feature extraction algorithms, including 2D holistic feature, 2D local feature, 3D holistic feature, and 3D local feature extraction algorithms, are then described in detail. Finally, feature selection and fusion techniques are presented. The article covers the complete related aspects of feature selection for 2D and 3D face recognition. Keywords: face biometrics; face identification; face recognition; face verification; feature extraction; feature selection
Fundamentals of Anatomy and Physiology

This text is designed specifically to meet the needs of a diverse student population. It offers three ways of covering real-world applications: Clinical Discussion; Clinical Boxes (which provide more in-depth coverage of major diseases); and the Applications Manual. The artwork is unusual in that it falls into three categories: Compound Art combines Bill Ober's award-winning illustrations with photographs, micrographs, X-rays, and MRI images; Process Art shows how the successive stages of dynamic physiology processes unfold in time; and Large Illustrations Viewed from a Macro-Micro Level, in context, help students better understand anatomical structures. As for the pedagogy, the book has four main features: Concept Checks, which are interspersed questions that encourage students to stop and check their understanding of material before they move on; Concept Links, that have page references to help students review concepts discussed earlier in the text; Figure Reference Locators, red squares next to call out figures in the text that function as placeholders to make it easier to toggle between illustrations and the running narrative; and Three-Level Chapter Ending Material - this moves students through memorizing facts, to understanding concepts, to applying what they learn to solve problems. Level One questions review basic facts and terms. Level Two questions test the student's ability to comprehend and integrate the chapter's key concepts. Level Three exercises are real world scenarios designed to develop student's problem solving skills.