Miracle-dz/UniFAR-FTUs huggingface dataset:
DISTRIBUTED SOURCE CODING FOR AN ACOUSTIC SENSOR ARRAY

Master of Electrical Engineering Program Cornell University Design Project Report Project Title: Distributed Source Coding for an Acoustic Sensor Array Author: Dennis Yueping Leung Abstract: This project aims to demonstrate the effectiveness of distributed source coding on audio sources. Exploring a technique proposed by Azadeh Vosoughi and Anna Scaglione, an encoder and decoder for this application were built. This involves compressing an audio source by using cosets or bins and trying to recover it using available side information. Additionally, the use of multiple instances of signal source to suppress noise was investigated. To accomplish the project goal, an acoustic sensor array was designed for the purpose of noise suppression. This sensor array was setup and used to collect experimental data to test the compression method. Then the data was encoded and decoded using a couple different structures. Performance calculations were done to demonstrate the usefulness of this compression method, even with real audio signals in practical applications, such as noise suppression. This project aims to demonstrate the effectiveness of distributed source coding on audio sources. Exploring a technique proposed by Azadeh Vosoughi and Anna Scaglione, an encoder and decoder for this application were built. This involves compressing an audio source by using cosets or bins and trying to recover it using available side information. Additionally, the use of multiple instances of signal source to suppress noise was investigated. To accomplish the project goal, an acoustic sensor array was designed for the purpose of noise suppression. This sensor array was setup and used to collect experimental data to test the compression method. Then the data was encoded and decoded using a couple different structures. Performance calculations were done to demonstrate the usefulness of this compression method, even with real audio signals in practical applications, such as noise suppression. Report Approved by Project Advisor:______________________________________Date:_________________
Treating malignant glioma in Chinese patients: update on temozolomide

Malignant glioma, ie, anaplastic astrocytoma and glioblastoma, is the most common type of primary malignant brain tumor in the People’s Republic of China, and is particularly aggressive. The median survival of patients with newly diagnosed glioblastoma is only 12–14 months despite advanced therapeutic strategies. Treatment of malignant glioma consists mainly of surgical resection followed by adjuvant radiation and chemotherapy. Temozolomide (TMZ), a second-generation oral alkylating agent, is playing an increasingly important role in the treatment of malignant glioma in Chinese patients. Since the publication of a study by Stupp et al in 2005, which used a protocol of conventional fractionated irradiation with concomitant TMZ followed by standard TMZ for six cycles, many clinical studies in the People’s Republic of China have demonstrated that such a treatment strategy has significantly improved efficacy with limited side effects for newly diagnosed glioblastoma after surgery as compared with strategies that do not contain TMZ. However, as a relatively new agent, the history and development of TMZ for malignant glioma is not well documented in Chinese patients. Multicenter, randomized controlled trials including appropriately sized patient populations investigating multiple aspects of TMZ therapy and related combination therapies are warranted in patients with malignant glioma. This review provides an update on the efficacy, mechanism of action, adverse reactions, and clinical role of TMZ in the treatment of malignant glioma in Chinese patients.
Pedestrian Detection with Semantic Regions of Interest

For many pedestrian detectors, background vs. foreground errors heavily influence the detection quality. Our main contribution is to design semantic regions of interest that extract the foreground target roughly to reduce the background vs. foreground errors of detectors. First, we generate a pedestrian heat map from the input image with a full convolutional neural network trained on the Caltech Pedestrian Dataset. Next, semantic regions of interest are extracted from the heat map by morphological image processing. Finally, the semantic regions of interest divide the whole image into foreground and background to assist the decision-making of detectors. We test our approach on the Caltech Pedestrian Detection Benchmark. With the help of our semantic regions of interest, the effects of the detectors have varying degrees of improvement. The best one exceeds the state-of-the-art.
EVALUATIONS OF AN ECHO SUPPRESSOR BASED ON A FREQUENCY-DOMAIN MODEL OF HIGHLY NONLINEAR RESIDUAL ECHO

This paper presents evaluations of a nonlinear-echo suppressor based on a frequency-domain model of highly nonlinear residual echo. The residual-echo model, which is based on correlation between spectral amplitudes of residual echo and echo replica, is evaluated by a regression analysis. The results justify the nonlinear-echo suppressor structure. The output signals are subjectively evaluated by mean opinion score (MOS). The score of the nonlinear-echo suppressor is superior to an echo canceller with a linear adaptive filter by 0.8 points on a 5-point scale. In implementation on a DSP system, it is shown that the nonlinear-echo suppressor requires 6.1 to 16.8 MIPS depending on the memory allocation.
Two-Party Computation Model for Privacy-Preserving Queries over Distributed Databases

Many existing privacy-preserving techniques for querying distributed databases of sensitive information do not scale for large databases due to the use of heavyweight cryptographic techniques. In addition, many of these protocols require several rounds of interactions between the participants which may be impractical in wide-area settings. At the other extreme, a trusted party based approach does provide scalability but it forces the individual databases to reveal private information to the central party. This paper shows how to perform various privacypreserving operations in a scalable manner under the honest-but-curious model. Our system provides the same level of scalability as a trusted central party based solution while providing privacy guarantees without the need for heavyweight cryptography. The key idea is to develop an alternative system model using a Two-Party Query Computation Model comprising of a randomizer and a computing engine which do not reveal any information between themselves. We also show how one can replace the randomizer by a lightweight key-agreement protocol. We formally prove the privacy-preserving properties of our protocols and demonstrate the scalability and practicality of our system using a real-world implementation.
A program complexity metric based on data flow information in control graphs

This paper presents a new approach to measuring program complexity with the use of data flow information in programs. A complexity metric, called DU, is defined for the control graph of a structured program. This new metric is different from other control-graph based metrics in that it is based on “representative” data flow information in a control graph. An algorithm for computing the value of DU(G) for a control graph G is given. The lower and upper bounds of DU(G) are provided. The DU metric is shown to have several advantages over other control-graph based complexity metrics.
Low levels of endogenous or X-ray-induced DNA double-strand breaks activate apoptosis in adult neural stem cells

ABSTRACT The embryonic neural stem cell compartment is characterised by rapid proliferation from embryonic day (E)11 to E16.5, high endogenous DNA double-strand break (DSB) formation and sensitive activation of apoptosis. Here, we ask whether DSBs arise in the adult neural stem cell compartments, the sub-ventricular zone (SVZ) of the lateral ventricles and the sub-granular zone (SGZ) of the hippocampal dentate gyrus, and whether they activate apoptosis. We used mice with a hypomorphic mutation in DNA ligase IV (Lig4Y288C), ataxia telangiectasia mutated (Atm−/−) and double mutant Atm−/−/Lig4Y288C mice. We demonstrate that, although DSBs do not arise at a high frequency in adult neural stem cells, the low numbers of DSBs that persist endogenously in Lig4Y288C mice or that are induced by low radiation doses can activate apoptosis. A temporal analysis shows that DSB levels in Lig4Y288C mice diminish gradually from the embryo to a steady state level in adult mice. The neonatal SVZ compartment of Lig4Y288C mice harbours diminished DSBs compared to its differentiated counterpart, suggesting a process selecting against unfit stem cells. Finally, we reveal high endogenous apoptosis in the developing SVZ of wild-type newborn mice. Summary: This study shows that endogenous and radiation-induced DNA damage sensitively activates apoptosis in the adult sub-ventricular zone (SVZ). Developmentally regulated apoptosis is shown in the neonatal SVZ.
Topometric localization on a road network

Current GPS-based devices have difficulty localizing in cases where the GPS signal is unavailable or insufficiently accurate. This paper presents an algorithm for localizing a vehicle on an arbitrary road network using vision, road curvature estimates, or a combination of both. The method uses an extension of topometric localization, which is a hybrid between topological and metric localization. The extension enables localization on a network of roads rather than just a single, non-branching route. The algorithm, which does not rely on GPS, is able to localize reliably in situations where GPS-based devices fail, including “urban canyons” in downtown areas and along ambiguous routes with parallel roads. We demonstrate the algorithm experimentally on several road networks in urban, suburban, and highway scenarios. We also evaluate the road curvature descriptor and show that it is effective when imagery is sparsely available.
Minimum estimation and combining generalized selection combining (MEC-GSC)

This paper introduces and analyzes a new adaptive minimum-estimation minimum-combining switched-combining based scheme that reduces considerably the average receiver channel estimation complexity and the power drain from the battery while satisfying a certain desired performance requirement. The mathematical formalism is supported by some selected numerical examples that show that the newly proposed combining scheme can essentially achieve the same performance as competing schemes such as generalized selection combining (GSC) while offering 50 % channel estimation and 75 % processing power savings for some system parameters of interest
The potential distribution of cassava mealybug (Phenacoccus manihoti), a threat to food security for the poor

The cassava mealybug is a clear and present threat to the food security and livelihoods of some of the world's most impoverished citizens. Niche models, such as CLIMEX, are useful tools to indicate where and when such threats may extend, and can assist with planning for biosecurity and the management of pest invasions. They can also contribute to bioeconomic analyses that underpin the allocation of resources to alleviate poverty. Because species can invade and establish in areas with climates that are different from those that are found in their native range, it is essential to define robust range-limiting mechanisms in niche models. To avoid spurious results when applied to novel climates, it is necessary to employ cross-validation techniques spanning different knowledge domains (e.g., distribution data, experimental results, phenological observations). We build upon and update a CLIMEX niche model by Parsa et al. (PloS ONE 7: e47675), correcting inconsistent parameters and re-fitting it based on a careful examination of geographical distribution data and relevant literature. Further, we consider the role of irrigation, the known distribution of cassava production and a targeted review of satellite imagery to refine, validate and interpret our model and results. In so doing, we bring new insights into the potential spread of this invasive insect, enabling us to identify potential bio-security threats and biological control opportunities. The fit of the revised model is improved, particularly in relation to the wet and dry limits to establishment, and the parameter values are biologically plausible and accord with published scientific literature.
LOAD FORECASTING BY A NOVEL TECHNIQUE USING ANN

Basically the active power demands at various load buses need to be estimated ahead of time in order to plan the generation and distribution schedules, for contingency analysis and also for monitoring the system security. A great deal of attention has been given in recent years to the question of setting up the demand models for the individual appliances and their impact on the aggregated demand. For the allocation of spinning reserve it would be necessary to predict the load demands at least an hour ahead. A method using ANN based technique is developed for short-term load forecast. The technique is tested on real time data collected from a 220 KV / 132 KV / 33 KV / 11 KV Renigunta Sub-Station, A.P, India. Calculations are done based on the hourly data of active power variations obtained over a period of one month. The active powers were used as input quantities for training the ANN and obtained the respective output active powers for the corresponding day.
Genetic resources and genomics for adaptation of livestock to climate change

Animal genetic resources (AnGR) are critical for global food security and livelihoods. Livestock products have high densities of energy, protein, and other critical nutrients, which are particularly beneficial for infants and expectant mothers. Around a billion people rely directly on livestock for their livelihoods, many of which are among the rural poor (FAO, 2009). Demand for animal products is foreseen to increase significantly in the future while competition for resources will intensify, dictating that livestock systems must increase both productivity and efficiency. Maintaining sufficient diversity of AnGR is necessary to ensure adaptation potential in times of uncertainty. In the future, climate change is expected to be a major force testing resilience of global food production systems (Thornton et al., 2009; Renaudeau et al., 2012). Ensuring that livestock systems remain productive and efficient while maintaining their flexibility will be a major challenge. Adaptation to climate change is unlikely to be achieved with a single strategy (Hoffmann, 2010). Clearly, modifications will be needed in animals' housing, reproduction, nutrition, and health care. Genetic changes in the animals (both within and across species) will also play a role. Preparation for these transformations will require a significant research commitment and genomics will play a role in the genetic measures taken for adaptation of livestock to climate change.
Proteomic identification of putative plasmodesmatal proteins from Chara corallina

Plasmodesmata are channels that bridge the cell walls of plant cells, allowing regulated transport of molecules between neighbouring cells. We have used a proteomic strategy to identify putative plasmodesmata‐associated proteins in the giant‐celled green alga Chara corallina. Proteins were extracted from the plasmodesmata‐rich nodal complexes and the middle of the long internodal cells, which do not contain plasmodesmata. Comparison of protein spot patterns generated by two‐dimensional gel electrophoresis of both the soluble and cell wall fractions from the two cell types was done. Fifty‐eight spots that were common to the nodal and internodal soluble fractions were analysed by matrix assisted laser desorption/ionisation‐time of flight mass spectrometry, and peptide mass fingerprint data were used to search the database. Matches were made to four of these spots, in each case to housekeeping proteins. Further, a number of nodal specific spots were identified, 11 from the soluble fraction and nine from the wall fraction. These spots were excised from the gels and analysed by liquid chromatography tandem mass spectrometry to obtain peptide sequence. Database searches suggest that these spots include homologues to previously identified plasmodesmata‐associated proteins cp‐wap13 and heat shock cognate 70, as well as RNA‐binding proteins, eukaryotic initiation factor 4A and a β‐1,3‐glucanase. Several spots remained unidentified providing exciting new candidate plasmodesmata‐associated proteins.
Generalized Time Related Sequential Association rule mining and traffic prediction

Time Related Association rule mining is a kind of sequence pattern mining for sequential databases. In this paper, we introduce a method of Generalized Association Rule Mining using Genetic Network Programming (GNP) with time series processing mechanism in order to find time related sequential rules efficiently. GNP represents solutions as directed graph structures, thus has compact structure and implicit memory function. The inherent features of GNP make it possible for GNP to work well especially in dynamic environments. GNP has been applied to generate time related candidate association rules as a tool using the database consisting of a large number of time related attributes. The aim of this algorithm is to better handle association rule extraction from the databases in a variety of time-related applications, especially in the traffic volume prediction problems. The generalized algorithm which can find the important time related association rules is described and experimental results are presented considering a traffic prediction problem.
An Adaptive Irregularly Spaced Fourier Method for Protein-Protein Docking ∗

In this paper we introduce a grid free irregularly sampled Fourier approach for accurately predicting rigid body protein-protein docking sites. Of the many docking approaches, grid based Fast Fourier Transform (FFT) approaches have been shown to produce by far the fastest, correlation profiles of complex protein-protein interactions over the six dimensional search space. However, these uniform sampling methods still possess high time complexity, and in particular, are highly memory intensive for predicting large protein-protein docking sites. By taking advantage of an irregularly and adaptively sampled, smooth particle representation of molecular shape, in combination with the use of irregularly spaced FFT transforms, we eliminate an explicit uniform grid. We are able to produce efficiently, highly compressed, but accurate, docking correlation profiles. This work was supported in part by NSF grants ACI-0220037, EIA-0325550, and NIH grants 0P20 RR020647, and R01 GM074258 julio@ices.utexas. edu bajaj@cs.utexas. edu skvinay@cs.utexas. edu
Clinical impact of inspiratory muscle impairment in sarcoidosis.

BACKGROUND AND AIM OF THE WORK We evaluated the clinical consequences of inspiratory muscle impairment on exercise tolerance and quality of life in 34 sarcoid patients compared with 19 controls. METHODS We measured pulmonary function tests, inspiratory muscle strength by maximal inspiratory pressure (PImax) and inspiratory muscle endurance (IME) by an incremental threshold loading test. IME was defined by the maximal sustainable pressure for 2 minutes (Plim2) and Plim2/PImax. Cycloergometer incremental exercise testing was performed in all patients. Health-related quality of life (HRQOL) was assessed by the SF-36 questionnaire in comparison with scores of 116 French controls. Dyspnea was assessed by the Modified Dyspnea Index (MDI). RESULTS All SF-36 subscales were lower in sarcoid patients (p < 0.05). PImax% pred was similar in both groups whereas IME was markedly lower in sarcoid patients (p < 0.0001). Plim2 correlated with MDI (r = 0.44; p = 0.01) and SF-36 scales Physical Functioning (PF) (r = 0.42; p = 0.034) and Physical Role (PR) (r = 0.63; p = 0.0016). Plim2/PImax correlated with SF-36 subscales: PR (r = 0.62), vitality (VT) (r = 0.56) and social functioning (SF) (r = 0.39). Plim2 (r = 0.639; p = 0.0002) and Plim2/PImax (r = 0.36; p = 0.036) correlated with peak exercise tidal volume (V(T)max) but not with VO2max. CONCLUSIONS Inspiratory muscle impairment was related to physical HRQOL scores but not to exercise tolerance, although it could impair exercising V(T) through an incipient inspiratory muscle fatigue.
Lightweight Protection of Group Content Distribution

Achieving security properties in distributed, hardware-limited, and unattended networks is a challenging task. This setting is challenging because an adversary can capture and physically compromise unattended nodes. In this setting, this paper presents one-way group communication protocols with strong security properties. In particular, how to send messages to a group of hardware-limited nodes with message secrecy and authenticity? We present several protocols and analyze them in terms of security, efficiency, and deployability. The resulting solutions are generic and can be useful in a variety of distributed systems.
Modification of saccadic eye movements by GABA-related substances. I. Effect of muscimol and bicuculline in monkey superior colliculus.

Our previous observations led to the hypothesis that cells in the substantia nigra pars reticulata (SNr) tonically inhibit saccade-related cells in the intermediate layers of the superior colliculus (SC). Before saccades to visual or remembered targets, cells in SNr briefly reduce that inhibition, allowing a burst of spikes of SC cells that, in turn, leads to the initiation of a saccadic eye movement. Since this inhibition is likely to be mediated by gamma-aminobutyric acid (GABA), we tested this hypothesis by injecting a GABA agonist (muscimol) or a GABA antagonist (bicuculline) into the superior colliculus and measured the effects on saccadic eye movements made to visual or remembered targets. An injection of muscimol selectively suppressed saccades to the movement field of the cells near the injection site. The affected area expanded over time, thus suggesting the diffusion of muscimol in the SC; the area never included the other hemifield, suggesting that the diffusion was limited to one SC. One of the monkeys became unable to make any saccades to the affected area. Saccades to visual targets following injection of muscimol had longer latency and slightly shorter amplitudes that were corrected by subsequent saccades. The most striking change was a decrease in the peak velocity of the saccade, frequently to less than half the preinjection value. Saccades to remembered targets following injection of muscimol also showed an increase in latency and decrease in velocity, but in addition, showed a striking decrease in the accuracy of the saccades. The trajectories of saccades became distorted as if they were deflected away from the affected area. After muscimol injection, the area over which spontaneous eye movements were made shifted toward the side ipsilateral to the injection. Saccades toward the contralateral side were less frequent and slower. In nystagmus, which developed later, the slow phase was toward the contralateral side. In contrast to muscimol, injection of bicuculline facilitated the initiation of saccades. Injection was followed almost immediately by stereotyped and apparently irrepressible saccades made toward the center of the movement field of the SC cells at the injection site. The monkeys became unable to fixate during the tasks; the fixation was interrupted by saccadic jerks made to the affected area of the visual field and then back to the fixation point. (ABSTRACT TRUNCATED AT 400 WORDS)