Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed attitude consensus among multiple networked spacecraft

In this paper we consider the distributed attitude consensus problem among multiple networked spacecraft in deep space, which extends the standard information consensus results in the literature to rigid body rotational dynamics. We propose control laws for three different cases. In the first case, multiple spacecraft align their attitudes during formation maneuvers with zero final angular velocities under an undirected communication topology. In the second case, attitudes are aligned in the presence of nonzero final angular velocities under an undirected communication topology. In the third case, attitude consensus under a directed information exchange topology is addressed. Simulation results for attitude consensus among six spacecraft show the effectiveness of our approach
Physical Changes in Satsuma Mandarin Leaf after Infection of Elsinoë fawcettii Causing Citrus Scab Disease

Citrus scab disease is one of the destructive diseases that reduce the value of fruit for the fresh market. We analyzed the process of symptom development after infection with scab pathogen Elsinoë fawcettii in the susceptible satsuma mandarin leaves to observe the structural modification against pathogen. The cuticle and epidermal cells along with 3–5 layers of mesophyll tissue were degraded 1–2 days post inoculation. Surrounding peripheral cells of degraded tissues grew rapidly and then enveloped the necrotic area along with the growing conidia. Cross sections through the lesion revealed hyphal colonization in epidermis and mesophyll tissues. In response to the pathogen colonization, host cell walls were lignified, inner cells were rapidly compartmentalized and a semi-circular boundary was formed that separated the infected region from the non-infected region, and finally prevented the intercellular pathogen spread.
Range Expansion and Inter-Cell Interference Coordination (ICIC) for Picocell Networks

Range expansion (RE), when applied with inter-cell interference coordination (ICIC) may have significant benefits for improving the throughput and fairness of macrocell/picocell networks. In this paper, first, benefits of RE in the uplink and downlink are reviewed, emphasizing its definitive merit for uplink communications. It is shown that while RE also improves the fairness in the downlink, it may seriously degrade the total system capacity if no ICIC is utilized. Then, a novel cell-selection technique that capitalizes on subframe-blanking at the macrocell is introduced for improving the downlink capacity and fairness. System level simulation results show that the proposed cellselection method adaptively achieves a good balance between sum capacity and fairness, and can be used in place of biasbased cell-selection.
Online constraint network optimization for efficient maximum likelihood map learning

In this paper, we address the problem of incrementally optimizing constraint networks for maximum likelihood map learning. Our approach allows a robot to efficiently compute configurations of the network with small errors while the robot moves through the environment. We apply a variant of stochastic gradient descent and use a tree-based parameterization of the nodes in the network. By integrating adaptive learning rates in the parameterization of the network, our algorithm can use previously computed solutions to determine the result of the next optimization run. Additionally, our approach updates only the parts of the network which are affected by the newly incorporated measurements and starts the optimization approach only if the new data reveals inconsistencies with the network constructed so far. These improvements yield an efficient solution for this class of online optimization problems. Our approach has been implemented and tested on simulated and on real data. We present comparisons to recently proposed online and offline methods that address the problem of optimizing constraint network. Experiments illustrate that our approach converges faster to a network configuration with small errors than the previous approaches.
Disfluency detection based on prosodic features for university lectures

This paper focuses on the identification of disfluent sequences and their distinct structural regions, based on acoustic and prosodic features. Reported experiments are based on a corpus of university lectures in European Portuguese, with roughly 32h, and a relatively high percentage of disfluencies (7.6%). The set of features automatically extracted from the corpus proved to be discriminant of the regions contained in the production of a disfluency. Several machine learning methods have been applied, but the best results were achieved using Classification and Regression Trees (CART). The set of features which was most informative for cross-region identification encompasses word duration ratios, word confidence score, silent ratios, and pitch and energy slopes. Features such as the number of phones and syllables per word proved to be more useful for the identification of the interregnum, whereas energy slopes were most suited for identifying the interruption point.
Great expectations: the value of spatial diversity in wireless networks

The effect of spatial diversity on the throughput and reliability of wireless networks is examined. Spatial diversity is realized through multiple independently fading transmit/receive antenna paths in single-user communication and through independently fading links in multiuser communication. Adopting spatial diversity as a central theme, we start by studying its information-theoretic foundations, then we illustrate its benefits across the physical (signal transmission/coding and receiver signal processing) and networking (resource allocation, routing, and applications) layers. Throughout the paper, we discuss engineering intuition and tradeoffs, emphasizing the strong interactions between the various network functionalities.
Sex Determination from Hand and Foot Bone Lengths *

ABSTRACT: Numerous studies have addressed sex estimation from the hands and feet with varying results. These studies have utilized multiple measurements to determine sex from the hands and feet, including measures of robusticity (e.g., base width and midshaft diameter). However, robusticity measurements are affected by activity, which can disguise underlying patterns of sexual dimorphism. The purpose of this study is to investigate the utility of length measurements of the hands and feet to estimate sex. The sample consists of white females (n=123) and males (n=136) from the Terry Collection. Discriminant function analysis was used to classify individuals by sex. The left hand outperformed both the right hand and foot producing correct classification rates exceeding 80%. Surprisingly, the phalanges were better sex discriminators than either the metacarpals or metatarsals. This study suggests that length measures are more appropriate than robusticity measures for sex estimation.
Expression of matrix metalloproteinase-9 in nasopharyngeal carcinoma and association with Epstein-Barr virus infection

Objective: To evaluate the expression of matrix metalloproteinase-9 (MMP9) in nasopharyngeal carcinoma and the association between MMP9 and Epstein-Barr virus infection. Methods: The MMP9 expression was studied by immunohistochemical analysis; and Epstein-Barr virus encoded small nuclear mRNA-1 (EBER-1) produced by in situ hybridization were examined in 41 nasopharyngeal carcinoma sections, and the relation between them, and the associations of MMP9 with clinical features were statistically analyzed. Results: Positive expression rate of MMP9 was 73.17%. The expression of MMP9 showed significant positive correlation with the expression of EBER-1 (γ=0.483, P=0.001). There was significant association of MMP9 expression with lymph nodes metastasis and clinical stage (P<0.001), non-significant association with age, gender, pathological classification and T classification. Conclusions: The highly pronounced expression of MMP9 is associated with cervical lymph nodes metastasis. Epstein-Barr virus can enhance NPC metastasis by up-regulating the expression of MMP9.
Influence of PWM switching frequency on the losses in PM machines

Using PWM converters to control electrical machines brings many benefits, such as improved dynamic behavior and energy savings, but also introduces a current ripple, which induces additional losses in the machine. This paper investigates the extent of these losses in the rotor, windings and laminations of a PM machine as function of switching frequency and dc-link voltage by means of a case study. It is found that particularly the rotor losses are very sensitive to the switching frequency; a high dc-link voltage and low switching frequency increase the rotor losses by an order of magnitude. The additional winding losses are divided in eddy-current losses, which remain a fraction of the dc winding losses at all times; and losses due to unequal current sharing over parallel strands, which can reach the same order of magnitude as the dc copper losses. The iron losses show the smallest increase due to the current ripple.
Exploiting the Immunomodulatory Properties of Chemotherapeutic Drugs to Improve the Success of Cancer Immunotherapy

Cancer immunotherapy is gaining momentum in the clinic. The current challenge is to understand why a proportion of cancer patients do not respond to cancer immunotherapy, and how this can be translated into the rational design of combinatorial cancer immunotherapy strategies aimed at maximizing success of immunotherapy. Here, we discuss how tumors orchestrate an immunosuppressive microenvironment, which contributes to their escape from immune attack. Relieving the immunosuppressive networks in cancer patients is an attractive strategy to extend the clinical success of cancer immunotherapy. Since the clinical availability of drugs specifically targeting immunosuppressive cells or mediators is still limited, an alternative strategy is to use conventional chemotherapy drugs with immunomodulatory properties to improve cancer immunotherapy. We summarize the preclinical and clinical studies that illustrate how the anti-tumor T cell response can be enhanced by chemotherapy-induced relief of immunosuppressive networks. Treatment strategies aimed at combining chemotherapy-induced relief of immunosuppression and T cell-boosting checkpoint inhibitors provide an attractive and clinically feasible approach to overcome intrinsic and acquired resistance to cancer immunotherapy, and to extend the clinical success of cancer immunotherapy.
Financial Openness and Productivity

Financial openness is often associated with higher rates of economic growth. We show that the impact of openness on factor productivity growth is more important than the effect on capital growth. This explains why the growth effects of liberalization appear to be largely permanent, not temporary. We attribute these permanent liberalization effects to the role financial openness plays in stock market and banking sector development, and to changes in the quality of institutions. We find some indirect evidence of higher investment efficiency post-liberalization. We also document threshold effects: countries that are more financially developed or have higher quality of institutions experience larger productivity growth responses. Finally, we show that the growth boost from openness outweighs the detrimental loss in growth from global or regional banking crises.
Exploring the Limits of Language Modeling

In this work we explore recent advances in Recurrent Neural Networks for large scale Language Modeling, a task central to language understanding. We extend current models to deal with two key challenges present in this task: corpora and vocabulary sizes, and complex, long term structure of language. We perform an exhaustive study on techniques such as character Convolutional Neural Networks or Long-Short Term Memory, on the One Billion Word Benchmark. Our best single model significantly improves state-of-the-art perplexity from 51.3 down to 30.0 (whilst reducing the number of parameters by a factor of 20), while an ensemble of models sets a new record by improving perplexity from 41.0 down to 23.7. We also release these models for the NLP and ML community to study and improve upon.
Required for B Cell Maintenance Antigen Dependent, and They Are Not Patches, Their Repertoire Development Is Lymphogenesis Is Absent in the Ileal Peyer's and Neonatal Piglets. XX. B Cell Antibody Repertoire Development in Fetal

The continuous ileal Peyer’s patches (IPP) of sheep are regarded as a type of mammalian bursal equivalent where B cells diversify their repertoire in an Ag-independent fashion. Anatomically and developmentally similar IPP occur in swine. Resection of ∼ 90% of the IPP in piglets at birth did not alter Ig levels in serum and secretions or retard diversiﬁcation of the Ab repertoire when animals were maintained in isolators and colonized with a deﬁned gut ﬂora. Resection or sham surgery elevated IgG and IgA in serum and in lavage ﬂuid from the gut, lung, and in saliva. No changes in the frequency of IgG-, IgA-, and IgM-containing cells in the spleen and peripheral lymph node were observed. Using an index that quantiﬁes diversiﬁcation of the VDJ repertoire, no differences were seen in three secondary lymphoid tissues between piglets lacking IPP and colonized controls, whereas both groups displayed >10-fold greater diversiﬁcation than did late-term fetal piglets or piglets maintained germ-free. Somatic hypermutation was very low in fetal IPP and the IPP of germ-free piglets but increased 3- to 5-fold after colonization. D–J signal joint circles were not recovered in IPP, and V–DJ signal joint circles were 5-fold lower than in bone marrow and similar to those in thymus and spleen. We conclude that the porcine IPP are not a site of B cell lymphogenesis, do not undergo Ag-independent repertoire diversiﬁcation, and are not primary lymphoid tissue since they are not required for maintenance of Ig levels in serum and secretions. The Journal of Immunology , 2011, 187: 000–000.
Biofilms of a Bacillus subtilis Hospital Isolate Protect Staphylococcus aureus from Biocide Action

The development of a biofilm constitutes a survival strategy by providing bacteria a protective environment safe from stresses such as microbicide action and can thus lead to important health-care problems. In this study, biofilm resistance of a Bacillus subtilis strain (called hereafter NDmedical) recently isolated from endoscope washer-disinfectors to peracetic acid was investigated and its ability to protect the pathogen Staphylococcus aureus in mixed biofilms was evaluated. Biocide action within Bacillus subtilis biofilms was visualised in real time using a non-invasive 4D confocal imaging method. The resistance of single species and mixed biofilms to peracetic acid was quantified using standard plate counting methods and their architecture was explored using confocal imaging and electronic microscopy. The results showed that the NDmedical strain demonstrates the ability to make very large amount of biofilm together with hyper-resistance to the concentration of PAA used in many formulations (3500 ppm). Evidences strongly suggest that the enhanced resistance of the NDmedical strain was related to the specific three-dimensional structure of the biofilm and the large amount of the extracellular matrix produced which can hinder the penetration of peracetic acid. When grown in mixed biofilm with Staphylococcus aureus, the NDmedical strain demonstrated the ability to protect the pathogen from PAA action, thus enabling its persistence in the environment. This work points out the ability of bacteria to adapt to an extremely hostile environment, and the necessity of considering multi-organism ecosystems instead of single species model to decipher the mechanisms of biofilm resistance to antimicrobials agents.
Early colonization of mutans streptococci in 2- to 36-month-old Thai children.

PURPOSE The purpose of this study was to determine the timing of colonization of streptococci mutans (SM) in 2- to 36-month-old Thai children. METHODS Two hundred and two 2- to 36-month-old children were divided into 3 groups: group 1 = 84 predentate children; group 2 = 68 children with 1 to 8 erupted teeth; and group 3 = 50 children with 9 to 20 erupted teeth. Microbiological samples were obtained from children by cotton swab. Samples were diluted and plated on mitis salivarius agar supplemented with Baocitracin (MSB) for selection and enumeration of SM. RESULTS SM colonization was found in 26% of children, who had a mean age in months of 20.5 +/- 103 (SD). MS colonization was detected in 5% of predentate children and was detected in children as young as 2 months old. The percentage of children who were colonized with SM rose significantly with increasing age and numbers of erupted teeth (P < .001). CONCLUSIONS Streptococci mutans colonization in 2- to 36-month-old Thai children was found in predentate children and detected in children as young as 2 months old. The results suggest that prevention of early SM colonization in some populations may need to be initiated prior to tooth eruption.
Logics of metric spaces

We investigate the expressive power and computational properties of two different types of languages intended for speaking about distances. First, we consider a first-order language FM the two-variable fragment of which turns out to be undecidable in the class of distance spaces validating the triangular inequality as well as in the class of all metric spaces. Yet, this two-variable fragment is decidable in various weaker classes of distance spaces. Second, we introduce a variable-free modal language MS that, when interpreted in metric spaces, has the same expressive power as the two-variable fragment of FM. We determine natural and expressive fragments of MS which are decidable in various classes of distance spaces validating the triangular inequality, in particular, the class of all metric spaces.
Depression, anxiety, and smartphone addiction in university students- A cross sectional study

Objectives The study aims to assess prevalence of smartphone addiction symptoms, and to ascertain whether depression or anxiety, independently, contributes to smartphone addiction level among a sample of Lebanese university students, while adjusting simultaneously for important sociodemographic, academic, lifestyle, personality trait, and smartphone-related variables. Methods A random sample of 688 undergraduate university students (mean age = 20.64 ±1.88 years; 53% men) completed a survey composed of a) questions about socio-demographics, academics, lifestyle behaviors, personality type, and smartphone use-related variables; b) 26-item Smartphone Addiction Inventory (SPAI) Scale; and c) brief screeners of depression and anxiety (PHQ-2 and GAD-2), which constitute the two core DSM-IV items for major depressive disorder and generalized anxiety disorder, respectively. Results Prevalence rates of smartphone-related compulsive behavior, functional impairment, tolerance and withdrawal symptoms were substantial. 35.9% felt tired during daytime due to late-night smartphone use, 38.1% acknowledged decreased sleep quality, and 35.8% slept less than four hours due to smartphone use more than once. Whereas gender, residence, work hours per week, faculty, academic performance (GPA), lifestyle habits (smoking and alcohol drinking), and religious practice did not associate with smartphone addiction score; personality type A, class (year 2 vs. year 3), younger age at first smartphone use, excessive use during a weekday, using it for entertainment and not using it to call family members, and having depression or anxiety, showed statistically significant associations with smartphone addiction. Depression and anxiety scores emerged as independent positive predictors of smartphone addiction, after adjustment for confounders. Conclusion Several independent positive predictors of smartphone addiction emerged including depression and anxiety. It could be that young adults with personality type A experiencing high stress level and low mood may lack positive stress coping mechanisms and mood management techniques and are thus highly susceptible to smartphone addiction.
Performance comparison of routing protocols under dynamic and static file transfer connections

We compare the performance of two recently proposed distance-vector algorithms (Merlin-Segall and Extended Bellman-Ford) with a link-state algorithm (SPF), under varying file transfer workload. (Unlike the traditional distance-vector algorithms, these new distance-vector algorithms do not suffer from long-lived loops.) Our comparison is done using a recently developed network simulator. MaRS. We consider both dynamic and static file transfer connections, and both uniform and hotspot distributions of source-sink pairs. Our conclusion is that Extended Bellman-Ford performs as well as SPF in terms of delay and throughput. This suggests that distance-vector algorithms are appropriate for very large wide-area networks, since their space requirements are less than that of link-state algorithms.
Agnostic PAC Learning of Functions on Analog Neural Nets

We consider learning on multilayer neural nets with piecewise polynomial activation functions and a fixed number k of numerical inputs. We exhibit arbitrarily large network architectures for which efficient and provably successful learning algorithms exist in the rather realistic refinement of Valiant’s model for probably approximately correct learning (”PAC learning”) where no a priori assumptions are required about the ”target function” (agnostic learning), arbitrary noise is permitted in the training sample, and the target outputs as well as the network outputs may be arbitrary reals. The number of computation steps of the learning algorithm LEARN that we construct is bounded by a polynomial in the bit-length n of the fixed number of input variables, in the bound s for the allowed bit-length of weights, in 1 / ~ , where E is some arbitrary given bound for the true error of the neural net after training, and in l / h where b is some arbitrary given bound for the probability that the learning algorithm fails for a randomly drawn training sample. However, the computation time of LEARN is exponential in the number of weights of the considered network architecture, and therefore only of interest for neural nets of small size. This article provides details to the previously published extended abstract (Maass 1994).
Energy-neutral source-channel coding in energy-harvesting wireless sensors

This work addresses the problem of energy allocation over source compression and transmission for a single energy-harvesting sensor. An optimal class of policies is identified that simultaneously guarantees a maximal average distortion and the stability of the queue connecting source and channel encoders, whenever this is feasible by any other strategy. This class of policies performs an independent resource optimization for the source and channel encoders. Analog transmission techniques as well as suboptimal strategies that do not use the energy buffer (battery) or use it only for adapting either source or channel encoder energy allocation are also studied.