Miracle-dz/UniFAR-FTUs huggingface dataset:
A Microfluidic Platform Containing Sidewall Microgrooves for Cell Positioning and Trapping

Microfluidic channels enable the control of cell positioning and the capturing of cells for high-throughput screening and other cellular applications. In this paper, a simple microfluidic platform is proposed for capturing small volumes of cells using sidewall microgrooves. The cell docking patterns in the channels containing sidewall microgroove are also studied. Both numerical and experimental investigations are performed within channels containing sidewall microgrooves of three different widths (i.e., 50, 100 and 200 μm). It is observed that channels containing sidewall microgrooves play an important role in regulating cell positioning and patterning. The obtained results revealed that 10 to 14 cells were positioned inside the sidewall channels of 200 μm width, two to five cells were positioned within the channels of 100 μm width, and one to two individual cells were docked within the sidewall channel of 50 μm width. Particle modelling shows the prediction of cell positioning within sidewall microgrooves. The positions of cells docked within microgroove-containing channels were also quantified. Furthermore, the shear stress variation and cell positioning in the sidewall microgrooves were correlated. Therefore, these sidewall microgroove-containing channels could be potentially useful for regulating cell positioning and patterning on two-dimensional surfaces, three-dimensional microenvironments and high-throughput screening. Cell patterning and positioning are of great importance in many biological applications, such as drug screening and cell-based biosensing.
Throughput Optimal Distributed Control of Stochastic Wireless Networks

The Maximum Differential Backlog (MDB) control policy of Tassiulas and Ephremides has been shown to adaptively maximize the stable throughput of multi-hop wireless networks with random traffic arrivals and queueing. The practical implementation of the MDB policy in wireless networks with mutually interfering links, however, requires the development of distributed optimization algorithms. Within the context of CDMA-based multi-hop wireless networks, we develop a set of node-based scaled gradient projection power control algorithms which solves the MDB optimization problem in a distributed manner using low communication overhead. As these algorithms require time to converge to a neighborhood of the optimum, the implementation of the MDB policy must be done with delayed queue state information. For this, we show that the MDB policy with delayed queue state information remains throughput optimal.
Double Virus Vector Infection to the Prefrontal Network of the Macaque Brain

To precisely understand how higher cognitive functions are implemented in the prefrontal network of the brain, optogenetic and pharmacogenetic methods to manipulate the signal transmission of a specific neural pathway are required. The application of these methods, however, has been mostly restricted to animals other than the primate, which is the best animal model to investigate higher cognitive functions. In this study, we used a double viral vector infection method in the prefrontal network of the macaque brain. This enabled us to express specific constructs into specific neurons that constitute a target pathway without use of germline genetic manipulation. The double-infection technique utilizes two different virus vectors in two monosynaptically connected areas. One is a vector which can locally infect cell bodies of projection neurons (local vector) and the other can retrogradely infect from axon terminals of the same projection neurons (retrograde vector). The retrograde vector incorporates the sequence which encodes Cre recombinase and the local vector incorporates the “Cre-On” FLEX double-floxed sequence in which a reporter protein (mCherry) was encoded. mCherry thus came to be expressed only in doubly infected projection neurons with these vectors. We applied this method to two macaque monkeys and targeted two different pathways in the prefrontal network: The pathway from the lateral prefrontal cortex to the caudate nucleus and the pathway from the lateral prefrontal cortex to the frontal eye field. As a result, mCherry-positive cells were observed in the lateral prefrontal cortex in all of the four injected hemispheres, indicating that the double virus vector transfection is workable in the prefrontal network of the macaque brain.
Sock Sorting

Algorithms of a social nature are extremely important and we are very dependent on certain “data structures” like names and social security numbers, on courts and on the postal system, and on various other social structures which enable us to perform activities like calling someone (you need her name for that), suing someone, or sending someone a bill. Unlike the situation in the theory of computation the existence of an algorithm for a real life situation always implies that the problem is feasibly solvable. Perhaps the closest to the unsolvability of the halting problem are Arrow’s [1] impossibility theorems for voting. In this paper we analyze a rather mundane problem the problem of sorting socks after they have come out of the dryer and give several polynomial time algorithms
Design of Fuzzy Cognitive Maps for Modeling Time Series

This study elaborates on a comprehensive design methodology of fuzzy cognitive maps (FCMs). Here, the maps are regarded as a modeling vehicle of time series. It is apparent that whereas time series are predominantly numeric, FCMs are abstract constructs operating at the level of abstract entities referred to as concepts and represented by the individual nodes of the map. We introduce a mechanism to represent a numeric time series in terms of information granules constructed in the space of amplitude and change of amplitude of the time series, which, in turn, gives rise to a collection of concepts forming the corresponding nodes of the FCMs. Each information granule is mapped onto a node (concept) of the map. We identify two fundamental design phases of FCMs, namely 1) formation of information granules mapping numeric data (time series) into activation levels of information granules (viz., the nodes of the map), and 2) optimization of information granules at the parametric level, viz., learning (estimating) the weights between the nodes of the map. The learning is typically realized in a supervised mode on a basis of some experimental data. A construction of information granules is realized with the aid of fuzzy clustering, namely fuzzy C-means. The optimization is realized with the use of particle swarm optimization. The proposed approach is illustrated in detail by a series of experiments using a collection of publicly available data.
Comparative Gene Mapping as a Tool to Understand the Evolution of Pest Crop Insect Chromosomes

The extent of the conservation of synteny and gene order in aphids has been previously investigated only by comparing a small subset of linkage groups between the pea aphid Acyrthosiphon pisum and a few other aphid species. Here we compared the localization of eight A. pisum scaffolds (covering more than 5 Mb and 83 genes) in respect to the Drosophila melanogaster Muller elements identifying orthologous loci spanning all the four A. pisum chromosomes. Comparison of the genetic maps revealed a conserved synteny across different loci suggesting that the study of the fruit fly Muller elements could favour the identification of chromosomal markers useful for the study of chromosomal rearrangements in aphids. A. pisum is the first aphid species to have its genome sequenced and the finding that there are several chromosomal regions in synteny between Diptera and Hemiptera indicates that the genomic tools developed in A. pisum will be broadly useful not only for the study of other aphids but also for other insect species.
'Cor placentale': placental intervillus/intravillus blood flow mismatch is the pathophysiological mechanism in severe intrauterine growth restriction due to uteroplacental disease.

The underlying pathophysiology in most cases of severe intrauterine growth restriction and pre-eclampsia is thought to be abnormal and inadequate conversion of the branches of the uterine arteries into low resistance uteroplacental vessels, due to poor extravillous trophoblastic invasion, leading to reduced intervillous blood flow. Since, in most vascular beds the main site of flow resistance is at the level of the small arteries/arterioles rather than the capillary bed itself it is likely that in cases of intrauterine growth restriction due to uteroplacental dysfunction with abnormal fetal umbilical artery flow velocity waveforms, the underlying pathological mechanism is primarily an initial reduction in intervillus flow leading to relative local hypoxia of some villus territories. This results initially in autocrine/paracrine mediated localized stem artery vasoconstriction to minimize intervillus/intravillus flow mismatch which, when widespread, will result in abnormal umbilical artery Doppler waveforms due to the globally increased resistance to fetoplacental flow. Since, a small reduction in vessel radius will result in an exponential increase in flow resistance and reduction in flow, the magnitude of stem vessel constriction need only be small to result in large changes in fetoplacental vascular haemodynamics. Thus, the underlying progressive pathology in this condition may be cardiac failure, secondary to chronic stem vessel vasoconstriction caused by abnormalities in oxygenation of the fetal respiratory system hence the term 'cor placentale' is proposed.
Explicit Minimum Storage Regenerating Codes

In distributed storage, a file is stored in a set of nodes and protected by erasure-correcting codes. Regenerating code is a type of code with two properties: first, it can reconstruct the entire file in the presence of any r node erasures for some specified integer r; second, it can efficiently repair an erased node from any subset of remaining nodes with a given size. In the repair process, the amount of information transmitted from each node normalized by the storage size per node is termed repair bandwidth (fraction). When the storage size per node is minimized, the repair bandwidth is lower bounded by 1/r, where r is the number of parity nodes. A code attaining this lower bound is said to have optimal repair. We consider codes with minimum storage size per node and optimal repair, called minimum storage regenerating (MSR) codes. In particular, if an MSR code has r parities and any r erasures occur, then by transmitting all the information from the remaining nodes, the original file can be reconstructed. On the other hand, if only one erasure occurs, only a fraction of 1/r of the information in each remaining node needs to be transmitted. If we view each node as a vector or a column over some field, then the code forms a 2-D array. Given the length of the column l and the number of parities r, we explicitly construct the high-rate MSR codes. The number of systematic nodes of our construction is (r + 1) logr l, which is longer than previously known results. Besides, we construct the MSR codes with other desirable properties: first, the codes with low complexity when the information is updated, and second, the codes with low access or storage node I/O cost during repair.
The basic science of brain-tumour gene therapy.

I 1 Chemajovsky, Y. , Adarns, G. , Podhajcer, 0. L. , Mueller, G. M. , Robbins, P. D. and Feldrnann, M. (I 995) Gene Ther. 2,73 1-735 12 Annenkov, A. E. , Moyes, S. P., Eshhar, Z. , Mageed, R A. and Chemaiovsky, Y. ( I 998) I. Imrnunol. 161, 6 6 W 6 6 I2 385-397 Support for these studies were provided by the Arthritis Research Campaign, The Wellcome Trust, Multiple Sclerosis Society of Great Britain and Northern Ireland, Nufield Foundation, British Council, CONICOR and Fundacion Antorchas (Argentina).
Hearing Loss

Hearing loss may be a sudden or a progressive impairment that gradually gets worse over time. Depending on the cause, it can be mild or severe, temporary or permanent. It may be a bilateral loss occurring in both ears or unilateral. Hearing loss may be caused by a number of factors, including: genetics, ageing, exposure to noise, some infections, birth complications, trauma to the ear, and certain medications or toxins. A common condition that results in hearing loss is chronic ear infections. Certain infections during pregnancy such as rubella may also cause problems.
SRAM design for nanoscale technology with Dynamic Vth and dynamic standby voltage for leakage reduction

Present mobile applications demand for devices with low power and high speed. With continuous technology scaling power dissipation due to leakage currents has became biggest challenges of VLSI industry in designing of these high speed and low power devices. With projected large memory con-tent of future systems on chip devices, it is important to consider the leakage current in Static Random Access Memory (SRAM) structures. Literature contains various proposed leakage current reduction techniques for SRAM cell such as Data retention gated ground scheme, Dynamic threshold, Multi threshold SRAM, Sleep transistor based SRAM etc. This work focuses on design of SRAM cell with dynamic Vth and dynamic standby voltage to mitigate the leakage power dissipation. Simulation results show significant reduction in power dissipation in standby mode of SRAM cell.
Neural Networks that Learn to Discriminate Similar Kanji Characters

A neural network is applied to the problem of recognizing Kanji characters. Using a back propagation network learning algorithm, a three-layered, feed-forward network is trained to recognize similar handwritten Kanji characters. In addition, two new methods are utilized to make training effective. The recognition accuracy was higher than that of conventional methods. An analysis of connection weights showed that trained networks can discern the hierarchical structure of Kanji characters. This strategy of trained networks makes high recognition accuracy possible. Our results suggest that neural networks are very effective for Kanji character recognition.
Expectation Semirings: Flexible EM for Learning Finite-State Transducers

Most recent work on finite-state transducers (FSTs) falls into two camps according to how the transducers are constructed. The algebraic camp employs experts who write (possibly weighted) regular expressions by hand, using an ever-growing language of powerful algebraic operators [10, 7]. The statistical camp, which prefers to extract expertise automatically from data, builds transducers with much simpler topology so that their arc probabilities can be easily trained (e.g., [17, 12, 11]). This paper offers a clean way to combine the two traditions: an Expectation-Maximation (EM) [4] algorithm for training arbitrary FSTs. First the human expert uses domain knowledge to specify the topology and parameterization of the transducer in any convenient way. Then the EM algorithm automatically chooses parameter values that (locally) maximize the joint likelihood of fully or partly observed data. Unlike previous specialized methods, the EM algorithm here allows transducers having ’s and arbitrary topology. It also allows parameterizations that are independent of the transducer topology (hence unaffected by determinization and minimization). But it remains surprisingly simple because all the difficult work can be subcontracted to existing algorithms for semiring-weighted automata. The trick is to use a novel semiring. To combine the two traditions, a domain expert might build a weighted transducer by using weighted expressions in the full finite-state calculus. Weighted regexps can also optionally refer to machines that are specified directly in terms of states, arcs, and weights, or even derived by approximating PCFGs [16]. But the various weights are written in terms of unknown parameters and estimated automatically. The semiring approach ensures that the method works even if the transducer is built with operations such as composition, directed replacement, and minimization, which distribute the parameters over the arcs in a complex way. This parameter estimation yields a transducer that models the joint probability P (x, y), where x and y are input and output strings. As usual, this transducer can easily be manipulated to obtain the marginal distributions P (x), P (y) and the conditional distributions P (x | y), P (y | x), and to find strings maximizing these distributions. For example, argmaxx∈X P (x | y ∈ Y ) = argmaxx∈X P (x, (y ∈ Y )) is the most likely underlying string in regular set X when the corresponding surface string is known to be in regular set Y . Learning weights for such transducers has many applications. Some examples:
Sonoelectrochemical Synthesis of Submicron Metal Powders

Pulsed sonoelectrochemical synthesis is a widely used technique for producing nanoparticles. In this technique, alternating pulses of electric current and power ultrasound are applied to an electrochemical cell to create and suspend particles in the electrolyte. The pulsed technique largely separates the particle morphology defining physical action of electrochemistry and ultrasound. Despite the large body of work characterizing the pulsed method, surprisingly little is written about the behavior of particles in the continuous case, where electric current and ultrasound are simultaneously present. In this thesis, continuous ultrasound assisted electrochemical synthesis of nanoparticles is established. Potentially useful mechanisms for particle size and shape control in continuous reactors are discussed. A continuous sonoelectrochemical reactor was designed and demonstrated to produce submicron copper powders. Improvements to the batch reactor design are proposed to extend the technique to a flow reactor useful for commercial production of submicron metal powders. Thesis Supervisor: Taofang Zeng Title: Principal Research Scientist
An efficient N-to-1 multipath routing protocol in wireless sensor networks

A typical task in a wireless sensor network is that every sensor node senses its local environment and, upon request, sends the data of interest back to a base station. Based on this many-to-one communication pattern, we first propose a distributed N-to-1 multipath discovery protocol which distinguishes from other multipath routing protocols in that it is able to find multiple node-disjoint paths from every sensor node to the base station simultaneously in one route discovery process. Then we propose a hybrid multipath data collection scheme which combines end-to-end multipath traffic dispersion and per-hop alternate path salvaging. Our simulation results show that the proposed N-to-1 multipath discovery protocol is highly efficient and the hybrid data collection scheme based on it provides a seamlessly more reliable and more secure data collection service in wireless sensor networks
An SR-protein induced by HSVI binding to cells functioning as a splicing inhibitor of viral pre-mRNA.

The interaction between a virus and its specific receptor on the membrane of the host cell mimics the physiological combination of signal ligand and its receptor, and initiates the specific signal transduction from this activated receptor to induce a relative gene response. During the investigation of the interaction between Herpes simplex virus I (HSVI) and human fibroblast via the virus binding to its receptor complex on the cellular membrane, a new gene of cellular response against the specific stimulation of HSVI binding to fibroblasts was cloned from a cDNA library established from mRNA of an early gene response. This gene encoded a protein of 14.9kDa with the structural characteristics of Arg-rich and RS repeats. The analysis of the role of this protein in the infection by HSVI indicated that this protein, expressed only in G(1)/S phase and phosphorylated, functioned as a splicing inhibitor of HSVI pre-mRNA. The details of the mechanism of this inhibition of HSVI pre-mRNA splicing is still unclear.
Targeting the Midgut Secreted PpChit1 Reduces Leishmania major Development in Its Natural Vector, the Sand Fly Phlebotomus papatasi

Background During its developmental cycle within the sand fly vector, Leishmania must survive an early proteolytic attack, escape the peritrophic matrix, and then adhere to the midgut epithelia in order to prevent excretion with remnants of the blood meal. These three steps are critical for the establishment of an infection within the vector and are linked to interactions controlling species-specific vector competence. PpChit1 is a midgut-specific chitinase from Phlebotomus papatasi presumably involved in maturation and degradation of the peritrophic matrix. Sand fly midgut chitinases, such as PpChit1, whether acting independently or in a synergistic manner with Leishmania-secreted chitinase, possibly play a role in the Leishmania escape from the endoperitrophic space. Thus, we predicted that silencing of sand fly chitinase will lead to reduction or elimination of Leishmania within the gut of the sand fly vector. Methodology/Principal Findings We used injection of dsRNA to induce knock down of PpChit1 transcripts (dsPpChit1) and assessed the effect on protein levels post blood meal (PBM) and on Leishmania major development within P. papatasi. Injection of dsPpChit1 led to a significant reduction of PpChit1 transcripts from 24 hours to 96 hours PBM. More importantly, dsPpChit1 led to a significant reduction in protein levels and in the number of Le. major present in the midgut of infected P. papatasi following a infective blood meal. Conclusion/Significance Our data supports targeting PpChit1 as a potential transmission blocking vaccine candidate against leishmaniasis.