Miracle-dz/UniFAR-FTUs huggingface dataset:
Enriching Human Interactome with Functional Mutations to Detect High-Impact Network Modules Underlying Complex Diseases

Progress in high-throughput -omics technologies moves us one step closer to the datacalypse in life sciences. In spite of the already generated volumes of data, our knowledge of the molecular mechanisms underlying complex genetic diseases remains limited. Increasing evidence shows that biological networks are essential, albeit not sufficient, for the better understanding of these mechanisms. The identification of disease-specific functional modules in the human interactome can provide a more focused insight into the mechanistic nature of the disease. However, carving a disease network module from the whole interactome is a difficult task. In this paper, we propose a computational framework, DIMSUM, which enables the integration of genome-wide association studies (GWAS), functional effects of mutations, and protein-protein interaction (PPI) network to improve disease module detection. Specifically, our approach incorporates and propagates the functional impact of non-synonymous single nucleotide polymorphisms (nsSNPs) on PPIs to implicate the genes that are most likely influenced by the disruptive mutations, and to identify the module with the greatest impact. Comparison against state-of-the-art seed-based module detection methods shows that our approach could yield modules that are biologically more relevant and have stronger association with the studied disease. We expect for our method to become a part of the common toolbox for disease module analysis, facilitating discovery of new disease markers.
Information use in foraging flocks of songbirds - no evidence for social transmission of patch quality

Animals use behavioural cues from others to make decisions in a variety of contexts. There is growing evidence, from a range of taxa, that information about the locations of food patches can spread through a population via social connections. However, it is not known whether information about the quality of potential food sources transmits similarly. We studied foraging behaviour in a population of wild songbirds with known social associations, and tested whether flock members use social information about the profitability of patches to inform their foraging decisions. We provided artificial patches (ephemeral bird feeders) that appeared identical but were either profitable (contained food) or unprofitable (contained no food). If information about patch profitability spreads via social associations, we predicted that empty feeders would only be sampled by individuals that are less connected to each other than expected by chance. In contrast, we found that individuals recorded at empty feeders were more closely associated with each other than predicted by a null model simulating random arrival of individuals, mirroring pattern of increased connectedness among individuals recorded at full feeders. We then simulated arrival under network-based diffusion of information, and demonstrate that the observed pattern at both full and empty feeders matches predictions derived from this post-hoc model. Our results suggest that foraging songbirds only use social cues about the location of potential food sources, but not their profitability. These findings agree with the hypothesis that individuals balance the relative economic costs of using different information, where the costs of personally sampling a patch upon arrival is low relative to the cost of searching for patches. This study extends previous work on information spread through avian social networks, by suggesting important links between how animals use information at different stages of the acquisition process and the emerging population-level patterns of patch use.
Process Analytical Technology for CO2 Capture

Carbon capture and storage, which is also known as CCS, is an obligatory climate change mitigation technology to reduce the carbon dioxide gas emissions to the atmosphere thus limiting the average global temperature increase to 2°C. Process analytical technology is a scientific tool to improve process qualities and performance through timely measurements. This chapter describes how process analytical technology can be imbedded to a carbon capture technology by giving a detailed example of implementation of a process analyzer to CO 2 capture by alkanolamine absorption process. Such an implementation requires suc - cess in five elements, which are described in this chapter. They are as follows: selecting an appropriate process analyzer, integration between the analyzer and the process, model development to enable the analyzer to predict a process-related chemical or physical attri -bute, use of the developed model in real-time application and use of the data obtained from the analyzer as an input to a process control unit. Partial least square regression model is a useful chemometric-based method to extract hidden chemical information in measure - ments from a process analyzer. In this chapter, four partial least square regression models are presented, which are developed to predict CO 2 concentration for four different alkanol - amine solutions when these amines are used to absorb CO 2 from a combustion process. resentative x variables. There can be various reasons for outliers such as impurities in samples, different sample type, instrument error and sampling errors. During the model development stage, if such outliers are identified, they should be carefully analyzed and removed from the model. When the model is used for process monitoring, visualization of such outliers helps in the quick identification of the abnormal behavior in the process. With the increasing number of PLS components, the prediction error of the models varies. A plot of RMSEP versus num ber of PLS components is used to conclude the required number of PLS components for the model. It is always preferable to select a small number of PLS components to avoid model complexities. An optimum number of PLS components avoids the risk of overfitting of the model. The aim of the model is to use the instrument for predicting CO 2 concentration. The predicted versus measured plots show how far the measured values deviate with respect to the predicted values for the validation set. This deviation is interpreted with statistical param eters such as r 2 , RMSEP and offset. When test set validation is used, this plot gives an image on how the model will align with future data.
TREATMENT OF SNAP BEAN PLANTS GROWN UNDER SANDY SOIL CONDITIONS WITH SOME NATURAL MATERIALS AND ITS RELATION TO GROWTH, YIELD AND POD QUALITY

Two field experiments were carried out during the fall seasons of 2012 and 2013 at the Agriculture Research Farm, El-Kassasien Hort. Res. Station, Ismalia Governorate, Egypt, and storage Lab. , Hort. Dept., Fac. of Agric. , Zagazig University, to study the effect of seed and soil inoculation (arbuscular mycorrhizal fungi, soil yeast) as well as foliar application with some natural materials (pigeon manure tea, compost tea, humic acid and effective microorganisms) on growth, photosynthetic pigments, yield and its components as well as chemical constituents of snap bean pods ( Phaseolus vulgaris L.) cv. Paulista. It aimed also to study the effect of the abovementioned treatments on snap bean pods storability during cold storage at 7 o C and 90-95% RH in different periods, i.e., 7, 14,21 and 28 days. Results show that there were significant increases in vegetative growth characters, photosynthetic pigments, yield and it's components as well as some chemical constituents of pods as a result of snap bean seeds inoculation with AMF plus application with soil yeast around root zone by using hand sprayer as compared to other treatments. Spraying snap bean plants with pigeon manure tea at 10g/L recorded maximum values of vegetative growth characters, photosynthetic pigments, yield and it's components as well as chemical constituents of pods followed by humic acid at 3cm 3 /L as compared to the control. The interaction treatment between dual inoculation with AMF and soil yeast and foliar spray with pigeon manure tea gave the highest values of vegetative growth characters, photosynthetic pigments, yield and it's components as well as chemical constituents of pods followed by the interaction treatment between dual inoculation with AMF and soil yeast and foliar spray with humic acid. Generally, quality parameters of snap bean pods during cold storage at 7 o C and 90-95 RH indicate that weight loss was increased, while dry matter, total carbohydrates and crude protein percentage in snap bean pods were decreased as the storage period prolonged up to 28 days from the beginning of storage period. Green pods obtained from plants treating by dual inoculation with AMF and soil yeast and sprayed with pigeon manure tea or humic acid and stored at 7 o C and 90-95 RH for 21 days was the best interaction treatment recorded the lowest values of weight loss and the best values of dry matter, total carbohydrates and crude protein percentage.
A New Modeling Method Considering Load Frequency Characteristics

Practice shows that the frequency characteristics of the load have important influence on analysising the safety and stability of the power grid. In order to improve the accuracy of the load model, a comprehensive load model considering load frequency characteristics is established based on the static load frequency factor and the frequency dependent part of induction motor model. For the parameter of the load model, a new composite modeling method based on the combination of statistical comprehensive method and measurement-based modeling approach is proposed to calculate and check the parameters of the model. Finally, a simulation example is given to illustrate the effectiveness of the proposed composite modeling method considering load frequency characteristics
Population genetic structure in Plantago ovata var. decumbens with using ISSR markers

Population genetic structure in Plantago ovata var. decumbens with using ISSR markers. - Genetika, Vol 51, No.2, 717-730. Plantago ovata (Plantaginaceae) is a medicinal plant cultivated extensively in Western Asia for seed husk known as blonde Psyllium or Isabgol. We used ISSR molecular markers to investigate the population genetic structure and genetic divergence within P. ovata populations. We identified P. ovata variety as var. decumbens based on the morphological data. WARD tree and PCoA plot produced similar results on morphological data. AMOVA revealed a significant genetic differentiation among the studied populations. STRUCTURE analyses showed some degree of gene flow among the studied populations. NJ tree and PCoA plot of ISSR data revealed that there are at least three genetic groups within the studied populations. Though the studied populations in P. ovata are genetically differentiated, there are not qualitative morphological features for differentiating among theirs. Therefore, we consider them as ecotypes within P. ovata.
A simulated annealing‐based maximum‐margin clustering algorithm

Maximum‐margin clustering is an extension of the support vector machine (SVM) to clustering. It partitions a set of unlabeled data into multiple groups by finding hyperplanes with the largest margins. Although existing algorithms have shown promising results, there is no guarantee of convergence of these algorithms to global solutions due to the nonconvexity of the optimization problem. In this paper, we propose a simulated annealing‐based algorithm that is able to mitigate the issue of local minima in the maximum‐margin clustering problem. The novelty of our algorithm is twofold, ie, (i) it comprises a comprehensive cluster modification scheme based on simulated annealing, and (ii) it introduces a new approach based on the combination of k‐means++ and SVM at each step of the annealing process. More precisely, k‐means++ is initially applied to extract subsets of the data points. Then, an unsupervised SVM is applied to improve the clustering results. Experimental results on various benchmark data sets (of up to over a million points) give evidence that the proposed algorithm is more effective at solving the clustering problem than a number of popular clustering algorithms.
Low-Cost Packaging of 300 GHz Integrated Circuits With an On-Chip Patch Antenna

Placing a 300 GHz on-chip patch antenna in a low-cost quad-flat no-lead (QFN) package using materials based on silica microparticles dispersed in an epoxy matrix can improve the antenna performance. Full-wave simulations of a rectangular patch antenna, compliant with the metal stack and design rules of a 65 nm complementary metal–oxide–semiconductor (CMOS) process, show 13% radiation efficiency, 1 dB peak antenna gain, and 7 GHz –10 dB |S11| bandwidth increases when the thickness of packaging material over the antenna is ∼λ/3. When placed in a QFN package, 276 GHz CMOS signal generators with the same on-chip antenna show the effective isotropic radiated power ∼6 dB higher than that of unpackaged. This improvement is partly attributed to the antenna performance enhancement and demonstrates that it is possible to package 300 GHz integrated circuits with an on-chip patch antenna using a low-cost technique.
Toward universal laws of technology evolution: modeling multi-century advances in mobile direct-fire systems

This paper explores the question of whether a single regularity of technological growth might apply to a broad range of technologies, over a period of multiple centuries. To this end, the paper investigates a collection of diverse weapon systems called here the mobile direct-fire systems. These include widely different families of technologies that span the period of 1300–2015 CE: foot soldiers armed with weapons from bows to assault rifles; horse-mounted soldiers with a variety of weapons; foot artillery and horse artillery; towed antitank guns; self-propelled antitank and assault guns; and tanks. The main contribution of this paper is that, indeed, a single, parsimonious regularity describes the historical growth of this extremely broad collection of systems. Multiple, widely different families of weapon systems—from a bowman to a tank—fall closely on the same curve, a simple function of time. This suggests a general model that unites allometric relations (such as Kleiber’s Law) and exponential growth relations (such as Moore’s Law). To this author’s knowledge, no prior research describes a regularity in the temporal growth of technology that covers such widely different technologies and over such a long period of history. This regularity is suitable for technology forecasting, as this paper illustrates with explorations of two systems that might appear 30 years in the future from this writing: a heavy infantryman and a tank. In both cases, the regularity helped lead to nonobvious conclusions, particularly regarding the power of the weapons of such future systems. Furthermore, this result suggests a possibility—and related research questions—that even broader collections of technology families might evolve historically in accordance with what might be called universal laws of technological evolution.
Pedestrians receptivity in autonomous vehicles: Exploring a video-based assessment

Pedestrian receptivity toward autonomous vehicles (AVs) usually depends on the extent to which they receive indication of the vehicle’s intended action. Previous studies have typically used overt subjective measures (trust measures, ratings, etc.) and few objective measures (walking speed, waiting time, etc.) to identify external features that can improve pedestrians’ receptivity toward AVs. The current study aims to evaluate pedestrians’ behavioral measures of receptivity based on their body (head and foot) movements as they experience an AV in a virtual traffic environment. Videos of pedestrians at a virtual crosswalk, interacting with an AV that was equipped with an external feature indicating different operator statuses were coded. The operator statuses used in this study included: no driver, attentive driver, and distracted driver. The external features used were: no feature, upraised hand, stop sign, walking silhouette, walk in text, music, and a verbal message. Pedestrian body movements were derived from the video to determine frequency for looking at the approaching vehicle while crossing and stops after initiating crossing. Average durations for initiating crossing after signal were calculated. For no feature condition, the waiting time was calculated when participants observed the car. Data were compared with pedestrians’ self-reported ratings for receptivity to investigate body movements’ sensitivity to participants’ receptivity level. Results suggest body movements are sensitive to individual differences in reported receptivity. Future work should further examine the utility of this behavioral metric by further examining situational differences.
Multicast and Broadcast Services Over Mobile Networks: A Survey on Standardized Approaches and Scientific Outcomes

Due to the increasing demand for pervasive video and broadcast-like applications, multicast and broadcast communications are expected to assume an important role in upcoming 5G systems. The current research trend is trying to reuse, extend, or adapt reference transmission strategies already designed for the conventional 4G technology. Nevertheless, apart the two reference and standardized methodologies, i.e., multimedia broadcast/multicast service and single cell-point to multipoint, many technical extensions and novel solutions were published in the literature so far. Therefore, in order to provide a clear overview on available solutions (already standardized or simply extending conventional approaches), the present work provides a comprehensive survey on network architectures, communication protocols, transmission strategies, and optimization algorithms to improve the performance of multicast communications over mobile radio systems. The core of the conducted study represents a structured taxonomy, able to properly classify scientific contributions based on their reference standard, targeted goal, addressed methodology, considered application domain, and obtained results. Taking into account this taxonomy, more than one hundred of scientific contributions are presented, classified, and reviewed. The study of the state-of-the-art is further enhanced with the discussion on important lessons learned, which clearly highlight the pros and cons of any investigated approach. A focus is also provided on the main issues on long term evolution multicasting that need to be better investigated, and determine the possible future research directions on this subject. The final goal of this paper is to support research activities devoted to the identification of promising methodologies, that efficiently support the delivery of real-time and on-demand video contents in a TV-like fashion.
On the Interaction Between Aggregators, Electricity Markets and Residential Demand Response Providers

To decarbonize the heating sector, residential consumers may install heat pumps. Coupled with heating loads with high thermal inertia, these thermostatically controlled loads may provide a significant source of demand side flexibility. Since the capacity of residential consumers is typically insufficient to take part in the day-ahead electricity market (DAM), aggregators act as mediators that monetize the flexibility of these loads through demand response (DR). In this paper, we study the strategic interactions between an aggregator, its consumers and the DAM using a bilevel optimization framework. The aggregator-consumer interaction is captured either as a Stackelberg or a Nash Bargaining Game, leveraging chance-constrained programming to model limited controllability of residential DR loads. The aggregator takes strategic positions in the DAM, considering the uncertainty on the market outcome, represented as a stochastic Stackelberg Game. Results show that the DR provider-aggregator cooperation may yield significant monetary benefits. The aggregator cost-effectively manages the uncertainty on the DAM outcome and the limited controllability of its consumers. The presented methodology may be used to assess the value of DR in a deregulated power system or may be directly integrated in the daily routine of DR aggregators.
AN IMPROVED METHOD OF BUSBAR VOLTAGE RECONSTRUCTION FROM SIGNALS OF ELECTRIC FIELD SENSORS INSTALLED IN AN INDOOR MV SUBSTATION

This paper presents an improved method for the reconstruction of busbar voltage waveforms from signals acquired by a system of electric field (EF) sensors located in an indoor medium voltage substation. In the previous work [8], the authors proposed the use of black-box models in the form of artificial neural networks (ANNs) for this task. In this paper it is shown that a parametric model of the system of EF sensors can reconstruct voltages with much lower errors, provided that it is accurately identified. The model identification is done by minimization of a nonlinear goal function, i.e. mean squared error (MSE) of voltage reconstruction. As a result of examining several optimization techniques, the method based on simulated annealing extended with a simplex search, is proposed. The performance of the model identified with this method is at least 8 times better in terms of MSE and at least 12 times better in terms of frequency domain errors than the best one of concurrent ANNs.
Adaptive Parallelism in Browsers

Author(s): Zambre, Rohit Shahaji | Advisor(s): Chandramowlishwaran, Aparna | Abstract: Mozilla Research is developing Servo, a parallel web browser engine, to exploit the benetsof parallelism and concurrency in the web rendering pipeline. Parallelization results inimproved performance for pinterest.com but not for google.com. This is because the workload of a browser is dependent on the web page it is rendering. In many cases, the overhead of creating, deleting, and coordinating parallel work outweighs any of its benets. In this work, I model the relationship between web page primitives and a web browser's parallelperformance and energy usage using both regression and classication learning algorithms.I propose a feature space that is representative of the parallelism available in a web pageand characterize it using seven key features. After training the models to minimize custom-dened loss functions, such a model can be used to predict the degree of parallelism availablein a web page and decide the optimal thread conguration to use to render a web page. Suchmodeling is critical for improving the browser's performance and minimizing its energy usage.As a case study, I evaluate the models on Servo's styling stage. Experiments on a quad-coreIntel Ivy Bridge (i7-3615QM) laptop show that we can improve performance and energyusage by up to 94.52% and 46.32% respectively on the 535 web pages considered in thisstudy. Looking forward, we identify opportunities to tackle this problem with an online-learningapproach to realize a practical and portable adaptive parallel browser on variousperformance- and energy-critical devices.