Miracle-dz/UniFAR-FTUs huggingface dataset:
Bone stromal production of insulin-like growth factor binding protein 5 promotes growth and survival of prostate cancer

Prostate cancer (PCa) is the most common cancer among Canadian men and is continuing to be the third-leading cause of male cancer death in Canada. PCa is initially androgen-dependent. Some patients developed metastasis at diagnosis, and are treated by androgen withdrawal therapy. The majority of patients will respond, resulting in tumor growth arrest. However, PCa eventually progresses to androgen-independence and no effective treatment is available. Stromalepithelial interaction is critical to PCa survival and proliferation. The bone metastasis in PCa indicated compatibility between bone stroma cells and PCa epithelial cells in bone microenvironment. IGF-I and IGF-II are the most abundant growth factors stored in bone. The bioavailability of IGF-I can be modulated by IGFBP-5, the most abundant IGFBP in bone stroma. IGFBP-5 is one of few consistently upregulated genes in mice bone stroma after castration. The functions of IGFs and IGFBP-5 are implicated in PCa growth and survival. The objective of this thesis was to investigate the role of stroma-derived IGFBP-5 in PCa bone metastasis and progression to androgen-independence. We generated IGFBP-5 expressing bone stroma MG63-BP5 clone, and its vector counterpart MG63-mock clone. We investigated the anti-apoptotic effect of MG63-BP5 conditioned medium on LNCaP PCa cells under androgendeprived condition through enhancing IGF-I-mediated survival signaling. We observed the ability of MG63 cells to support LNCaP tumor formation in nude mice coinoculated with LNCaP/MG63 cells. We also observed an increase in growth rate and PSA level in LNCaP/MG63-BP5 xenografts compared to LNCaP/MG63-mock xenografts both in intact and castrated mice. Immunohistochemical staining of these xenografts showed no difference in proliferation, however decreased apoptosis was seen in LNCaP/MG63-BP5 xenografts. Our study is the first to demonstrate that bone stroma-produced paracrine IGFBP-5 played a role in bone microenvironment that favors PCa cell survival as well as androgen-independent progression. We propose that IGFBP-5 can act as a reservoir for IGF-I that allows slowly release of IGF-I for receptor interactions, resulting in amplification of downstream signaling pathways, which promote cell survival. We concluded that this is an adaptive mechanism for PCa to resist undergoing apoptosis and survive under androgen deprivation stress. T A B L E O F C O N T E N T S Abstracts ii Table of
Nitrogen leaching from grassland in Lithuania

Leaching losses from the soil contribute to undesired nutrients loads into surface water. It was the aim of the presented paper to give an overview of nitrogen (N) leach­ ing losses from long-term drained cultivated grassland in relation to land use in Lithuania. In comparison with mown grassland (MG), the soil bulk density decreased between 2 and 9 % in set-aside grassland (SAG) within a 6-year period of investigation. Mineralization of the grass residues in spring increased the nitrate nitrogen (NO 3 -N) content 1.5 - 2.0-fold in the SAG compared with the MG treatment. Correspondingly, the NO 3 -N concentration in the drainage flow was 1.5 times higher. The mean annual NO 3 -N and total nitrogen (N tot ) leaching losses from the MG plots were 1.7 ± 0.9 and 7.9 ± 3.0 kg ha -1 yr -1 , respec­ tively. In comparison, the leaching losses from SAG that was not fertilized were 4.0 ± 1.5 NO 3 -N kg ha -1 yr -1 and 11.6 ± 3.2 kg N tot ha -1 yr -1 . Fertilization of MG with 60 kg N ha -1 had no significant influence on the NO 3 -N content in the soil and drainage flow. Ploughing the grassland (PG) and sowing of spring cereals increased the NO 3 -N content in the soil by 15 to 40 mg kg , but losses decreased after two years to values of 5 to 11 mg kg -1 . The NO 3 -N and N tot concentration in the drainage flow increased by 3.5 - 6.1 and 6.2 - 9.1 mg L -1 , respectively. Leaching losses were 12.4 kg NO 3 -N ha -1 yr -1 and 20.0 kg N tot ha -1 yr -1 . After two years, the leaching losses varied only slightly between 2.0 and 5.0 kg N tot ha -1 yr -1 .
Standing stock and production of phytoplankton in the northern South China Sea during winter of 2006

Standing stock and production of phytoplankton in the northern South China Sea (nSCS) were studied during February 2006 when northeast monsoon strongly prevailed. The results clearly showed that the distributions of phytoplankton were closely related to the physical-chemical-biological coupled processes driven by the northeast monsoon. The chlorophyll-a (Chl a) concentration varied from 0.03 mg·m-3 to 1.21 mg·m-3 (the average value was (0.33±0.33) mg·m-3). The most of high values appeared in the coast areas near Guangdong Province and in the sea area to the east of Hainan Island. The lowest and highest value of primary production (PP) were 41.3 mgC·m-2·d-1 and 1040.0 mgC·m-2·d-1. The distribution patterns of Chl a differed from PP in three different regions. As for Chl a,coastal region ((0.53±0.50) mg·m-3) had much higher value than open sea ((0.31±0.30) mg m-3) and shelf region ((0.20±0.11) mg·m-3); as for PP,the variation showed opposite:open sea had the highest value ((631.3±578.0) mgC·m-2·d-1),followed by shelf (162.2 mgC·m-2·d-1) and coastal region (41.3 mgC·m-2·d-1) in turn. Photosynthetic picoplankton was found to be the greatest contributor to phytoplankton stocks and production in all study area,especially in open sea,47% and 66% respectively.
Theory of Surface States

The properties of metal-to-semiconductor junctions and of free semiconductor surfaces are usually explained on the basis of surface states. The theory of the metal contacts is discussed critically, because strictly speaking localized surface states cannot exist in such junctions. However, it is shown that virtual or resonance surface states can exist which behave for practical purposes in the same way. They are really the tails of the metal wave functions rather than separate states. In the past, the length of this tail has often been ignored. Some estimates of its length are made and its consequences pointed out. A semiquantitative discussion is given of various recent data, including the effect of an oxide layer on barrier height, the variation of barrier height with the metal, the work function of a free surface at high doping, and the effect of a cesium layer on the work function.
A taper function for Pseudotsuga menziesii plantations in Spain

Five stem taper models belonging to three different taper function categories were fitted to data corresponding to 282 Pseudotsuga menziesii trees. The trees were selected in the area surrounding 61 research plots installed in Galicia, Asturias and the Basque Country, northern Spain. The models were simultaneously fitted to observed values of diameter outside bark and inside bark. A third-order continuous-time autoregressive error structure was used to account for autocorrelation. Selection of the best model was based on both numerical (goodness-of-fit statistics) and graphical analysis (plots of residuals against position along the stem and against tree size). The three-segmented taper model finally selected has the advantage of being compatible with both a merchantable and a total stem volume equation.
Evaluation of Common Bean (Phaseolus vulgaris L.) Varieties for Resistance to Bean Stem Maggot (Ophiomyia spp .) in Kenya

Common bean is the most important pulse crop in Kenya, though small scale farmers involved in its farming have limited access to quality seeds resistant to pests such as bean stem maggot, thereby limiting its production from potential yield production of 2000 kg ha -1 to less than 1000 kg ha -1 . This study was therefore aimed at determining effective ways of managing bean stem maggot through identification and selection of resistant commercial varieties for enhanced host resistance. This was achieved through screening levels of resistance among commercial varieties and determining severity and incidence of bean stem maggot infestations. The study was conducted in Kakamega, Njoro and Uasin-gishu. The varieties were planted together with two local checks; KK 8, Tasha, KK
Preliminary Study on the Near-Field Absorber

This work proposes a new kind of absorber working in the near-field (NF). We first demonstrate that the conventional meta-surface absorber placed in the NF of an electric dipole is not able to consume the radiation power in the forward direction, which is due to its large reflection of the evanescent waves in the NF. Further, we propose a preliminary design of a NF absorber by using a highly capacitive surface. The example shows that the NF absorber is able to interact with the evanescent waves and could consume most of the radiation power and thus suppress omnidirectional electromagnetic interference (EMI).
Bio-efficacy of Synthetic Pyrethroids against Brinjal Shoot and Fruit borer, Leucinodes orbonalis (Guen.)

A field experiment was carried out during Rabi season 2002, to evaluate the bio-efficacy of cypermethrin applied at @ 0.003, 0.006 and 0.01%, and fenvalerate applied at @ 0.004, 0.008 and 0.015% concentrations against brinjal shoot and fruit borer, Leucinodes orbonalls (Guen.) on brinjal var. ‘Pusa Purple Round’ along with endosulfan @ 0.07%. All insecttcidal treatments gave effective control of shoot and fruit borers and increased yield of fruit over control. However, no significant difference was recorded among the treatments in reducing the shoot damage after 7cl of spraying. Plots treated with cypermethrin 0.006% and fenvalerate 0.015% recorded the 28.25% shoot damage at 7 d after spray. Yield was maximum (96.91 q ha−1) in cypermethrin 0.006% treated plots, followed by cypermethrin 0.01% (93.83 q ha−1), which was more than endosulfan 0.07% treated plots (68.58 q ha−1)
Effects of Social Touch from an Agent in Virtual Space: Comparing Visual Stimuli and Virtual-Tactile Stimuli

Although social touch in physical space has been scrutinized for its positive effects on people, the effects of social touch in virtual space has been neglected. In virtual space, two types of social touch can be designed, a touch with only visual stimuli and a touch with both visual and tactile stimuli. This paper investigates the effects of the two types of agent’s social touch on users in the context where the agent praises their performance of a task in virtual space. Based on past studies of social touch, we hypothesized that the two types of agent’s social touch in virtual space would improve the user’s task motivation, task performance, and the agent’s likability. We experimentally tested our hypotheses by comparing those variables among no-touch, visual-touch, and visual-tactile touch groups. Since our results showed no significant differences among these groups, our hypotheses were not supported. However, a post-hoc analysis by gender suggests that the agent’s social touch with both visual and tactile stimuli while praising male users increased their task motivation in virtual space. This result suggests that the effects of an agent’s social touch in virtual space may be different due to genders, and shows a possibility of positive effects for the touch behavior design of the agent in virtual space.
Planning mm-Wave Access Networks Under Obstacle Blockages: A Reliability-Aware Approach

Millimeter-wave (mm-wave) technologies are the main driver to deliver the multiple-Gbps promise in next-generation wireless access networks. However, the GHz-bandwidth potential must coexist with a harsh propagation environment. While strong attenuations can be compensated by directional antenna arrays, the severe impact of obstacle blockages can only be mitigated by smart resource allocation techniques. Multi-connectivity, as multiple mm-wave links from a mobile device to different base stations, is one of them. However, the higher reliability provided by several access alternatives can be fully exploited only if uncorrelated link statuses are guaranteed. Therefore, spatial diversity must be enforced. Moreover, since interposing obstacles can block a link, short access links allow reducing the link unavailability probability. Smart base-station selections can be made once the network is deployed, however, our results show that much better results are achievable if spatial diversity and link-length aspects are directly included in the network planning phase. In this article, we propose an mm-wave access network planning framework that considers base-station spatial diversity, link lengths, and achievable user throughput, according to channel conditions and network congestion. The comparison against traditional k-coverage approaches shows that our approach can obtain much better access reliability, thus providing higher robustness to random obstacles and self-blockage phenomena.
A 40-m Range 90-frames/s CMOS Time-of-Flight Sensor Using SPAD and In-Pixel Time-Gated Pulse Counter

This letter presents a CMOS indirect time-of-flight (i-ToF) image sensor, which is based on a single-photon avalanche diode (SPAD) and a compact in-pixel time-gated pulse counter. The proposed SPAD-based i-ToF sensor makes it possible to achieve a time-gated photon counting method at the pixel level and to enlarge a depth range up to 40 m while maintaining the pixel demodulation frequency up to 25 MHz. A prototype sensor is implemented in a 110-nm CMOS process and has a pixel array of <inline-formula> <tex-math notation="LaTeX">$64\times64$ </tex-math></inline-formula> with a pixel pitch of <inline-formula> <tex-math notation="LaTeX">$32~{\mu }\text{m}$ </tex-math></inline-formula>. With a 3-D frame rate of 90 frames/s, the sensor achieves high 3-D image quality with a nonlinearity error below 2.25% and a relative precision error of 0.51% at a maximum distance of 40 m.
Model Mediated Teleoperation with a Hand-Arm Exoskeleton in Long Time Delays Using Reinforcement Learning

Telerobotic systems must adapt to new environmental conditions and deal with high uncertainty caused by long-time delays. As one of the best alternatives to human-level intelligence, Reinforcement Learning (RL) may offer a solution to cope with these issues. This paper proposes to integrate RL with the Model Mediated Teleoperation (MMT) concept. The teleoperator interacts with a simulated virtual environment, which provides instant feedback. Whereas feedback from the real environment is delayed, feedback from the model is instantaneous, leading to high transparency. The MMT is realized in combination with an intelligent system with two layers. The first layer utilizes Dynamic Movement Primitives (DMP) which accounts for certain changes in the avatar environment. And, the second layer addresses the problems caused by uncertainty in the model using RL methods. Augmented reality was also provided to fuse the avatar device and virtual environment models for the teleoperator. Implemented on DLR’s Exodex Adam hand-arm haptic exoskeleton, the results show RL methods are able to find different solutions when changes are applied to the object position after the demonstration. The results also show DMPs to be effective at adapting to new conditions where there is no uncertainty involved.
Adaptive Sum of Markov Chains for Modelling 3D Blockage in mmWave V2I Communications

Blockage attenuation is one of the main challenges that face reliable communication at the millimetre-wave (mmWave) band, especially for dynamic vehicle-to-infrastructure (V2I) communication systems. Modelling the dynamics of the blockage is important for evaluating high gain beamforming techniques, which are used to improve the signal strength in the mmWave communication systems. The novel sum of Markov chains (sum of MC) model is designed to do two main tasks successfully; capturing the dynamics of blockers affecting a moving transceiver and computing the arising channel attenuation. The sum of MC model has advantages over existing Markov chains models, which are: that it can adapt to model non-stationary scenarios. The sum of MC model can integrate any attenuation function, including the 3GPP blockage model and any lab measurement attenuation profile. Additionally, it is computationally efficient. The sum of MC model can match well with the performance results from a more complex geometric channel model.
Mapping Network Traffic Dynamics in the Complexity-Entropy Plane

Network traffic plays a critical role in network planning and control. The researchers assume that traffic from Ethernet and other IP-related networks have a self-similar nature: high-variability and long-term correlations. Many studies try to model these characteristics for simulation and further optimization. One of the most straightforward approaches to model these characteristics is to consider ON/OFF sources (packet-train), where ON- and OFF-periods are i.i. d. , generated with random heavy-tailed distributions. Using information theory quantifiers, in particular the Causality Complexity-Entropy Plane, we show that heavy-tailed distributions do not capture most of the network traffic dynamics. They only reproduce the stochastic dynamics of traffic, which accounts for one of the smallest parts of it. We conduct this study by observing the Abilene dataset, fitting the log-normal and log-logistic distributions, and evaluating them onto Causality Complexity-Entropy Plane in comparison with 1/f-noise, which is one of the most observed long-term correlated noises in nature stochastic processes. Also, to enhance our illustrated results, we use the k-nearest-neighbors (kNN) to classify the real and generated traffic according to the results obtained. Finally, our results show that the dynamics of real network traffic does not match the fitting curves generally presented for synthetic traffic generators.
Automation of Vulnerability Classification from its Description using Machine Learning

Vulnerability reports play an important role in cybersecurity. Mitigation of software vulnerabilities that can be exploited by attackers depends on disclosure of vulnerabilities. Information on vulnerability types or identifiers facilitates automation of vulnerability management, statistical analysis of vulnerability trends, and secure software development. Labeling of reports with vulnerability identifiers has thus far been per-formed manually and has therefore suffered from human-induced errors and scalability issues due to the shortage of security experts. In this paper, we propose a scheme that automatically classifies each vulnerability description by type using machine learning. We experimentally demonstrated the performance of our proposed scheme compared to other algorithms, analyzed cases of misclassification, and revealed the potential for numerous human errors. We experimentally demonstrated the performance of the proposed scheme in comparison with other algorithms, analyzed cases of misclassification, and revealed the potential for numerous human errors. Furthermore, we tried to correct these errors.
Security Constrained MODGTEP using Adaptive Hybrid Meta-heuristic Approach

Due to the ever-increasing electricity demand, network expansion solutions from the Transmission Constrained Generation Expansion Planning (TC-GEP) process may not be adequate and thus the transmission network needs be expanded together with the generation system. Separation of the two processes of network expansion whose results must be combined during implementation will often lead to sub-optimal expansion plans. This concern has given rise to the integrated Generation and Transmission Expansion Planning (GTEP) optimization problem. In this paper the GTEP problem is formulated in a multi-objective and dynamic environment. The multi-objective function considers investment, production and outage costs as well as penalties related to system voltage violations and active power loss. In addition, the proposed formulation considers system redundancy. To increase on the reliability of the results the formulations are based on AC power flow models. The formulated MOGTEP problem is optimized using adaptive hybrid meta-heuristic approach. This approach is suitable for handling the highly dimensional and complex problem. The obtained results showed the superiority of the proposed MODGTEP formulation and solution methodology to other reviewed solution techniques. The proposed methodology produced less costly and more reliable expansion plans. Inclusion of the contingency analysis led to increase in the committed elements (generators and transmission lines) so as to account for any planned and forced outages in the system.
Effect of Root/Leaf Temperature Differentials on Root/Shoot Ratios in Some Pasture Grasses and Clover

Twelve pasture species were grown in the same aerial environment, but with five constant soil temperatures ranging from 5 to 35 °C, to determine the influence of root temperature on the weight of roots per unit weight of foliage (R/S ratio). This ratio varied by a factor of 2 to 8 within species. Using maximum yield of foliage to indicate the optimum soil temperature for each species, it was found that the R/S ratio was lowest at the optimum soil temperature, and was progressively higher at soil temperatures above and below the optimum with only slight exceptions. This experimental manipulation of R/S ratios suggests that the partitioning of photosynthate is controlled by the relative rates of photosynthesis and root absorption, by inverse proportion: Root mass x rate(akSOrption) a Leaf mass x rate (photosynthesis)'
Harnessing Hardware Defects for Improving Wireless Link Performance

The design trade-offs of transceiver hardware are crucial to the performance of wireless systems. In this paper, we present an in-depth study to characterize the surprisingly notable systemic impacts of low-pass filter (LPF) design, which is a small yet indispensable component used for shaping spectrum and rejecting interference. Using a bottom-up approach, we examine how signal-level distortions caused by the trade-off of LPF design propagate to the upper-layers of wireless communication, reshaping bit error patterns and degrading link performance of today’s 802.11 systems. Moreover, we propose a novel algorithm that harnesses LPF defects for improving video streaming, which substantially enhances video quality in mobile environments.
UAV-based Surveillance System: an Anomaly Detection Approach

Recent advancements in avionics and electronics systems led to the increased use of Unmanned Aerial Vehicles (UAVs) in several military and civilian missions. One of the main advantages that makes UAVs attractive is their ability to reach remote regions that are inaccessible to human operators, i.e. provide new aerial perspective in visual surveillance. Autonomous visual surveillance systems require real time anomalies detection. However, there are many difficulties associated with automatic anomalies detection by an UAV, as there is a lack in the proposed contributions describing abnormal events detection in videos recorded by a drone. In this paper, we propose an anomaly detection approach in a surveillance mission where videos are acquired by an UAV. We combine deep features extracted using a pretrained Convolutional Neural Network (CNN) with an unsupervised classification method, namely One Class Support Vector Machine (OCSVM). The quantitative results obtained on the used dataset show that our proposed method achieves good results in comparison to existing technique with an Area Under Curve (AUC) of 0.93.
Direct organogenesis and plant regeneration in preconditioned tissue cultures of Lathyrus cicera L., L. ochrus (L.)DC. and L. sativus L.

This study demonstrates the importance of preconditioning of source tissue in regeneration of multiple shoot buds from several species of Lathyrus. Preconditioned multiple shoots of Lathyrus cicera L. , L. ochrus (L.)DC. and L. sativus L. were obtained by germinating seeds on Murashige and Skoog (MS) medium containing 50 μM N 6 -benzylaminopurine (BAP) for 2 to 3 weeks. Multiple shoot bud formation occurred when epicotyl explants of preconditioned shoots were cultured on MS medium containing 5-50 μM BAP