Miracle-dz/UniFAR-FTUs huggingface dataset:
A systematic study of the cell wall composition of Kluyveromyces lactis

In many ascomycetous yeasts, the cell wall is composed of two main types of macromolecules: (a) polysaccharides, with a high content of β‐1,6‐ and β‐1,3‐linked glucan chains and minor amounts of chitin; and (b) cell wall proteins of different types. Synthesis and maintenance of these macromolecules respond to environmental changes, which are sensed by the cell wall integrity (CWI) signal transduction pathway. We here present a first systematic analysis of the cell wall composition of the milk yeast, Kluyveromyces lactis. Electron microscopic analyses revealed that exponentially growing cells of K. lactis supplied with glucose as a carbon source have a wall thickness of 64 nm, as compared to 105 nm when growing on 3% ethanol. Despite their increased wall thickness, ethanol‐grown cells were more sensitive to the presence of zymolyase in the growth medium. Mass spectrometric analysis identified 22 covalently linked cell wall proteins, including 19 GPI‐modified proteins and two Pir wall proteins. Importantly, the composition of the cell wall glycoproteome depended on carbon source and growth phase. Our results clearly illustrate the dynamic nature of the cell wall of K. lactis and provide a firm base for studying its regulation. Copyright © 2010 John Wiley & Sons, Ltd.
A unified approach to bandwidth allocation and access control in fast packet-switched networks

The authors present an approach to computing access control parameters as a function of both source characteristics and bandwidth allocation in the network. The technique relies on a fluid-flow model for the source, the leaky bucket rate control system, and the bandwidth allocation process. The methodology is suitable for any high-speed packet switching architecture. The approach allows for the real-time setting of the access control at a connection setup. It ensures that the access control mechanism is near transparent as long as connections behave as expected, while protecting the network from most misbehaving connections. Although some extreme cases have the potential to affect the network, they are essentially due to limitations inherent in the leaky bucket itself. <<ETX>>
Dynamic facial expression analysis based on extended spatio-temporal histogram of oriented gradients

Facial expression is crucial for proper analysis of a person's face. It is an indicator of the emotion of a person and thus has attracted the attention of many researchers. In this work, a novel local spatio-temporal descriptor is proposed for motion pattern detection. The proposed feature comprises histogram of 3D gradients and the gradients' variation over time to robustly describe the spatial and temporal information. It also incorporates spatio-temporal pyramid structure to handle different resolution and frame rate. To reduce the dimension of the feature, we applied genetic algorithm for region-based feature selection. We evaluated the performance of our proposed descriptors on facial expression recognition using the Cohn-Kanade CK
Reliability investigation and mechanism analysis for a novel bonding method of flexible substrate in 3D integration

A breakthrough in vertical stacking and bonding method in flexible substrates is developed and presented in this paper. Unlike current ACF and NCP approaches, which are used in most manufacturing industry, our novel stacking method uses only metal thin film as bonding material. Two different bonding material bumps are carried out in our experiment. Both show better electrical and reliability outcomes compared to current methods. Our proposed method can reach ultra-fine pitch, metal bonding without polymer material, simplified manufacturing process, better electrical performance and less reliability issues. It can be considered as a future bendable and flexible substrate stacking approach.
A novel test scheme for NAND flash memory based on built-in oscillator ring

Physical defects in the cells of the NAND Flash memory fluctuate the current flowing through the memory string. Two oscillator ring based test schemes for NAND Flash memory are proposed. The oscillator ring scheme for single column has good diagnostic capability, and the double ring scheme are sensitive to both SA0/SA1 faults and some soft errors. Experimental results validated the effectiveness of these methods.
Decision-tree inspired classification algorithm to detect Tuberculosis (TB)

Pakistan has the fifth highest incidence of Tuberculosis (TB) in the world. The current tests for TB diagnosis are smear and culture tests which have accuracies of about 40% and 70% respectively. They are inefficient, complicated and relatively expensive to perform in developing countries. In this paper, we present a novel computational predictive algorithm by modifying the standard decision tree that allows us to efficiently detect TB with high accuracy. It employs supervised learning to classify the samples into patients and healthy groups based on MFI values of different antibodies with an accuracy of about 94%, outperforming the traditional classifiers including decision trees, kNN, random forests and support vector machines (SVM). Our algorithm allows simultaneous, bench-top analysis of thousands of samples per day, does not rely on highly skilled or technical staff and provides easily interpretable results. Our work strongly suggests that developing, testing and implementing automated diagnostic algorithms such as ours can be helpful in overcoming infrastructural and human-resource constraints in poorly resourced countries.
Development Impact Assessment (DIA) Case Study. South Africa

This case study reviews South Africa’s experience in considering the impacts of climate change action on development goals, focusing on the South African energy sector and development impact assessments (DIAs) that have and could be used to influence energy policy or inform the selection of energy activities. It includes a review of assessments—conducted by government ministries, technical partners, and academic institutes and non-governmental organizations (NGOs)—that consider employment, health, and water implications of possible energy sector actions, as well as multi-criteria impact assessments.
Conservation post-récolte des céréales en zone sud-soudanienne du Burkina Faso : Perception paysanne et évaluation des stocks

La conservation post recolte des denrees alimentaires demeure un probleme majeur en Afrique subsaharienne. Une enquete visant a apprehender la perception paysanne de la conservation post recolte des cereales et une evaluation d’echantillons preleves dans les stocks de six localites du Burkina Faso ont ete realisees. Les resultats de l’enquete montrent que la majorite des producteurs conservent leurs recoltes de mil, de mais et de sorgho dans des greniers. L’usage de substances vegetales est la methode la plus repandue pour la conservation des cereales. De l’avis des producteurs, le mil serait la cereale qui se conserve le mieux (P<0,05). 71% des producteurs stipulent que la majorite des pertes post-recoltes sont imputables aux insectes. L’analyse au laboratoire des echantillons collectes a permis d’identifier 11 especes de depredateurs dans les stocks de cereales ; Rhyzopertha dominica F. est l'espece la plus abondante. Mots cles : Conservation post-recolte, Cereales, Insectes depredateurs, Pratiques endogenes.
Automatic verbal aggression detection for Russian and American imageboards

The problem of aggression for Internet communities is rampant. Anonymous forums usually called imageboards are notorious for their aggressive and deviant behaviour even in comparison with other Internet communities. This study is aimed at studying ways of automatic detection of verbal expression of aggression for the most popular American (4chan.org) and Russian (2ch.hk) imageboards. A set of 1,802,789 messages was used for this study. The machine learning algorithm word2vec was applied to detect the state of aggression. A decent result is obtained for English (88%), the results for Russian are yet to be improved.
Variable-Latency Floating-Point Multipliers for Low-Power Applications

This paper proposes a variable-latency floating-point multiplier architecture, which is compliant with IEEE 754-1985 and suitable for low-power applications. The architecture splits the significand multiplier into the upper and lower parts, and predicts the carry bit, sticky bit, and significand product from the upper part. In the case of correct prediction, the computation of lower part is disabled and the rounding operation is significantly simplified so that the floating-point multiplication can consume less power, and be completed early while maintaining the correct IEEE rounding and product. Experimental results show that the proposed multiplier can save respectable power and energy when compared to the fast multiplier at the expense of slight area and acceptable delay overheads.
MEMS-based Heating Element for in-situ Dynamical Experiments on FIB/SEM Systems

In-situ observation of microstructural evolution of solids such as recrystallization, grain growth and phase changes in SEM is important for various fields of material science and industry research. This technique requires reliable discrimination of differently oriented crystal phases combined with useful spatial and temporal resolution and with fast and precise control of specimen temperature. While the requirements on spatial and temporal resolution are satisfied by current SEMs with resolution below 1 nm and 100 Hz frame rate, existing heating holders for bulk samples only allow for heating rates up to 300ºC per minute (5ºC/s). Long ramping time, which is required during heating experiments done using these devices, may cause unwanted sample changes (e.g. oxidation or recrystallization) before the temperature range of interest is reached. Thermal radiation of massive heating holders decreases quality of material contrast imaging as the commonly used detectors of backscattered electrons become saturated by thermally emitted photons. MEMS-based heating holder [1], [2] in combination with in-situ site specific sample preparation using a FIB/SEM system brings significant improvement in instrumentation for in-situ heating experiments inside the SEM chamber. Low heated mass achieved by MEMS technology and heating control integrated into FIB/SEM system enable the user to perform dynamical experiments with heating rate in the order of 10 5 °C/s. The design of the MEMS heating chip and its controller assure temperature stability within 1°C after only few tens of miliseconds from heating start. At 1000°C, the central heating plate shows good temperature uniformity with less than 1% deviation from the target temperature [1]. The MEMS chip can be repeatedly heated up to 1300°C in vacuum conditions without performance loss [1]. Very low heating power of several mW does not bring limitation to the detection of any FIB/SEM signal (SE, BSE, secondary ions) including characteristic X-rays and EBSD
Intermolecular domain docking in the hairpin ribozyme

The hairpin ribozyme is a prototype small, self-cleaving RNA motif. It exists naturally as a four-way RNA junction containing two internal loops on adjoining arms. These two loops interact in a cation-driven docking step prior to chemical catalysis to form a tightly integrated structure, with dramatic changes occurring in the conformation of each loop upon docking. We investigate the thermodynamics and kinetics of the docking process using constructs in which loop A and loop B reside on separate molecules. Using a novel CD difference assay to isolate the effects of metal ions linked to domain docking, we find the intermolecular docking process to be driven by sub-millimolar concentrations of the exchange-inert Co(NH3)63+. RNA self-cleavage requires binding of lower-affinity ions with greater apparent cooperativity than the docking process itself, implying that, even in the absence of direct coordination to RNA, metal ions play a catalytic role in hairpin ribozyme function beyond simply driving loop-loop docking. Surface plasmon resonance assays reveal remarkably slow molecular association, given the relatively tight loop-loop interaction. This observation is consistent with a “double conformational capture” model in which only collisions between loop A and loop B molecules that are simultaneously in minor, docking-competent conformations are productive for binding.
Incidence of injury and attitudes to injury management in skilled flute players.

OBJECTIVE The flute is a highly popular instrument, yet little is known about the potential injury association with playing this instrument. PARTICIPANTS Twenty flautists from a major music training institution volunteered to participate in this project, and had played the flute for a minimum of ten years. METHODS A specifically designed musicians' health questionnaire was used to determine injury rates in a group of skilled collegiate flute players majoring in music to examine self-reported perceptions of performance-related musculoskeletal disorder causation and approaches to managing these conditions. RESULTS All except one player reported suffering from a performance-related musculoskeletal disorder, with pain present for longer than 3 months in two thirds of this group. The most common approach by the flautists was to take Alexander lessons rather than seeking health professional advice. Most attributed their symptoms to long hours of practice, poor posture and the presence of performance anxiety. CONCLUSIONS Flautists in this sample reported high rates of performance-related musculoskeletal disorders with the majority having been present for longer than 3 months. The approach to management often did not involve consultation with a health professional qualified to diagnose musculoskeletal conditions.
P5: Programmable Parsers with Packet-level Parallel Processing for FPGA-based Switches

This paper presents P5, a programmable packet parser with packet-level parallel processing for FPGA-based switches. P5 overcomes both limitations. First, P5 has the programmability of dynamically updating parsing algorithms at run-time. Second, P5 exploits packet-level parallelism in the bottleneck of parsing pipeline to compensate FPGA’s low clock frequency, and reduces resource consumption through a one-block recirculated strategy.
Matrix block formulation of closed-loop memoryless Stackelberg strategy for discrete-time games

Stackelberg strategies with closed-loop information structure are well known to be delicate to design in general. Nevertheless when they are restricted to the case of memoryless ones, that is when the controls are function of the time and the current state, then they are strongly time consistent. Due to this property, it is possible to compute step by step backward in time the value functions associated with the Stackelberg equilibrium. A new method, using a matrix block formulation is provided here to facilitate this numerical computation. An example illustrates this method.
Kidnapping Detection and Recognition in Previous Unknown Environment

An unaware event referred to as kidnapping makes the estimation result of localization incorrect. In a previous unknown environment, incorrect localization result causes incorrect mapping result in Simultaneous Localization and Mapping (SLAM) by kidnapping. In this situation, the explored area and unexplored area are divided to make the kidnapping recovery difficult. To provide sufficient information on kidnapping, a framework to judge whether kidnapping has occurred and to identify the type of kidnapping with filter-based SLAM is proposed. The framework is called double kidnapping detection and recognition (DKDR) by performing two checks before and after the “update” process with different metrics in real time. To explain one of the principles of DKDR, we describe a property of filter-based SLAM that corrects the mapping result of the environment using the current observations after the “update” process. Two classical filter-based SLAM algorithms, Extend Kalman Filter (EKF) SLAM and Particle Filter (PF) SLAM, are modified to show that DKDR can be simply and widely applied in existing filter-based SLAM algorithms. Furthermore, a technique to determine the adapted thresholds of metrics in real time without previous data is presented. Both simulated and experimental results demonstrate the validity and accuracy of the proposed method.
Analyzing blood cell image to distinguish its abnormalities (poster session)

In this paper, we show the blood-cell image classification system to be able to analyze and distinguish blood cells in the peripheral blood image. To distinguish their abnormalities, we segment red and white-blood cell in an image acquired from microscope with CCD camera and then, apply the various feature extraction algorithms to classify them. In addition to, we use neural network model to reduce multi-variate feature number based on PCA(Principal Component Analysis) to make classifier more efficient. Finally we show that our system has a good experimental result and can be applied to build an aiding system for pathologist.
researchers ’ collaboration relationships : A gender analysis of access to scientific information Africa

Women are underrepresented in STEM fields, particularly at higher levels of organizations. This paper investigates the impact this underrepresentation has on the processes of interpersonal collaboration in nanotechnology. Analyses are conducted to assess: 1) the comparative tie strength of women’s and men’s collaborations; 2) whether women and men gain equal access to scientific information through collaborators; 3) which tie characteristics are associated with access to information for women and men; and 4) whether women and men acquire equivalent amounts of information by strengthening ties. Our results show that overall tie strength is less for women’s collaborations, and that women acquire less strategic information through collaborators. Women and men rely on different tie characteristics in accessing information, but are equally effective in acquiring additional information resources by strengthening ties. The paper demonstrates that the underrepresentation of women in STEM impacts on the interpersonal processes of scientific collaboration, to the disadvantage of women scientists. Corresponding Author Africa Villanueva-Felez, INGENIO (CSIC-UPV), Universitat Politècnica de València, Ciudad Politécnica de la Innovatión, Edif. 8E 4o, Camino de Vera s/n, 46022, Valencia, Spain. Email: africa.villanueva@ingenio.upv. es
Multi-Leg Seat Inventory Control Based on EMSU and Virtual Bucket

Expected marginal seat revenue (EMSR) is a well-known method for airline seat inventory control airlines. However, this method employs a static model to study the dynamic reservation process, and does not take into account the risk tolerance of policy makers. Expected marginal seat utility (EMSU) replaces revenue by utility, which addresses the real situation of seat inventory control. However, there is still a lack of multi-leg seat control algorithms based on EMSU. Therefore, using EMSU and bucket algorithms, this paper applies the Markov decision-making process to simulate the flight reservation process and builds a dynamic multi-leg seat inventory control model. Experimental results validate the effectiveness of the proposed method.
Cautious Operation Planning Under Uncertainties

This paper deals with day-ahead power systems security planning under uncertainties by posing an optimization problem over a set of power injection scenarios that could show up the next day and modeling the next day's real-time control strategies aiming at ensuring security with respect to contingencies by a combination of preventive and corrective controls. We seek to determine whether and which day-ahead decisions must be taken so that, for scenarios over the next day, there still exists an acceptable combination of preventive and corrective controls ensuring system security for any postulated contingency. We formulate this task as a three-stage feasibility checking problem, where the first stage corresponds to day-ahead decisions, the second stage to preventive control actions, and the third stage to corrective post-contingency controls. We propose a solution approach based on the problem decomposition into successive optimal power flow (OPF) and security-constrained optimal power flow (SCOPF) problems of a special type. Our approach is illustrated on the Nordic32 system and on a 1203-bus model of a real-life system.
Segmental radiofrequency ablation of pulmonary vein ostia for patients with refractory paroxysmal atrial fibrillation using multi-slice spiral computed tomography guidance

Objective: To evaluate the safety and clinical efficacy of segmental radiofrequency ablation of pulmonary vein (PV) ostia for patients with refractory paroxysmal atrial fibrillation (AF) under multi-slice spiral computed tomography (MSCT) guidance before the procedure. Methods: A series of 58 consecutive patients with refractory paroxysmal AF were enrolled to undergo segmental radiofrequency ablation of PV ostia. The 36 male and 22 female patients with mean age of (57.4±9.5) (32:_79) years and no obvious organic heart disease. Before ablation, patients received MSCT to generate 3-dimentional image of the left atrium (LA) and proximal PVs. Patients then underwent segmental radiofrequency ablation of PV ostia using PV circular mapping catheter manipulated several times to ensure complete isolation between PVs and LA. Results: No complications occurred during the procedure. One patient developed delayed cardiac tamponade, which was drained percutaneously. The mean follow-up time was (17.1±9.3) months. Forty-one patients (95%) experienced improved quality of life one month after the procedure. Thirty-six patients (83%) showed stable sinus rhythm, while 10 patients (23%) required additional anti-arrhythmic drugs. AF returned≥1 time in 6 (14%) patients who underwent anti-arrhythmic drug therapy, but the number of episodes was less than that before the procedure. However, one patient experienced recurrent episodes of atrial flutter. Conclusion: It is safe and effective to perform segmental radiofrequency ablation of PV ostia for patients with refractory paroxysmal AF using MSCT guidance mappening.
A New Approach to Real Time Line Outage Contingency Analysis for Voltage Secure Operation of Power Systems

A new approach to ANN-based real time line outage contingency analysis for voltage security assessment in a power system has been proposed in this paper. In this approach a separate ANN has been trained for each of the vulnerable load buses in the system from the voltage stability point of view. The vulnerable load buses of the system are identified by modal analysis of the system reduced Jacobian (of Q-V coupling) matrix. The output obtained from each of these ANN's is the "distance to voltage collapse" in terms of the MVAR margin available at the specific vulnerable load bus corresponding to the current operating point (loading condition) of the system. The novel inputs proposed for these ANN's consist of the complex power contributions of each of the generators and other controllable reactive power sources provided in the system in meeting the load at the particular load bus at the current loading condition and the electrical distances between these sources and the load bus, in addition to the conventionally used inputs of reactive power margins at the sources and the complex power drawn by and the voltage magnitude at the particular load bus. These special inputs have been proposed essentially to take care of two types of evolving voltage instability processes in a system viz. the reactive power sources gradually exhausting their limits as well as the transmission system approaching its maximum power transfer capabilities.