Miracle-dz/UniFAR-FTUs huggingface dataset:
Classifying MEG 20 Hz Rhythmic Signals of Left , Right Index Finger Movement And Resting State Using Cascaded Radial Basis Function Networks

A cascaded Radial-Basis Functions (RBF) network was devised to classify the magnetoencephalography (MEG) rhythmic signals of the left, right index finger movement and resting state. Four right-handed subjects were instructed to perform self-paced index finger lifting in a rate of every 8 sec. MEG epochs from 4000 ms pre-movement to 3000 ms post-movement were digitized. Each trial was decomposed by Principal Component Analysis (PCA) and the task-related components were selected to reconstruct data followed by band-passed filtering around 16-20 Hz. Every five filtered epochs were averaged and processed by the Hilbert transform to produce a beta-band envelope. All the envelopes around sensorimotor channels were normalized and down-sampled to 100 samples. A movement feature vector was defined by concatenating two mean envelopes in the left and right channels. We defined a resting feature vector by averaging five envelopes randomly selected in the left and right channels respectively during the resting state, and then concatenating two means. Two cascaded 3-layer RBF networks were constructed in which the first RBF network was to discriminate the movement from the resting state, while the second one was to distinguish the left and right index finger movement. The classification rates (rest, left, right) for four subjects achieve (100, 91, 66)%, (100, 80, 72)%, (100, 76, 73)% and, (100, 74, 94)%, respectively.
Web-based Startup Success Prediction

We consider the problem of predicting the success of startup companies at their early development stages. We formulate the task as predicting whether a company that has already secured initial (seed or angel) funding will attract a further round of investment in a given period of time. Previous work on this task has mostly been restricted to mining structured data sources, such as databases of the startup ecosystem consisting of investors, incubators and startups. Instead, we investigate the potential of using web-based open sources for the startup success prediction task and model the task using a very rich set of signals from such sources. In particular, we enrich structured data about the startup ecosystem with information from a business- and employment-oriented social networking service and from the web in general. Using these signals, we train a robust machine learning pipeline encompassing multiple base models using gradient boosting. We show that utilizing companies' mentions on the Web yields a substantial performance boost in comparison to only using structured data about the startup ecosystem. We also provide a thorough analysis of the obtained model that allows one to obtain insights into both the types of useful signals discoverable on the Web and market mechanisms underlying the funding process.
Key Policy Attribute Based Encryption in Cloud Storage

Cloud Computing is the rapid growing technology and enables highly scalable services to be easily consumed over the Internet on an as-needed basis. It is a kind of Internet-based computing that provides shared processing resources and data to computers and other devices. Cloud computing has become a highly demanded service or utility due to the advantages of high computing power, cheap cost of services, high performance, scalability, accessibility as well as availability. Some cloud vendors are experiencing growth rates of 50% per year but being still in a stage of infancy, it has pitfalls that need to be addressed to make cloud computing services more reliable and user friendly. Data sharing is an important functionality in cloud storage. The proposed system provides how to maintain integrity, confidentiality and availability to share data with others. Here described new Attribute Based Encryption cryptosystems which generates encryption, decryption time along with file size. Proposed work explains encryption with Attribute Based encryption then file is spitted into chunks. Hash key is generated for every data chunk which is unique. Secure hash algorithm is used for generation of hash key. For decryption file is searched on cloud, with private key then it is decrypted. Attribute Based encryption along with secure hash algorithm is applied. This proposed work describes analysis of encryption, decryption time calculated with Identity Based encryption and Attribute Based encryption according to file size. It creates hash key for every chunk which is unique. Proposed algorithm gives confidentiality to work as it is a public key encryption algorithm of cryptography. It is also asymmetric i.e. key set is used for data encryption and decryption. Data is stored on cloud means it is available to everyone through Cloud space. Key generated for encryption and decryption is runtime. In this work analysis is there. Encryption and decryption time required by Identity Based Encryption and Attribute Based Encryption is calculated for comparison purpose. Both algorithms user can apply on different file type such as pdf, ppt, doc, mp3, jpg and file size.
Using Mobile Technologies for eBusiness Infrastructure in Kenyan Rural Micro and Small Enterprises: Hype or Opportunity?

The number of mobile telephone subscribers has grown steadily (CCK 2009) since the liberalization of the Kenyan telecommunications sub-sector through the 1997 Communications Act (KCA 2008). This has seen increased Mobile technologies penetration in the rural areas. Mobile telephones are the first telecommunications infrastructure in most Kenyan rural enterprises. As has been seen in the case of Bangladesh (Lawson C & N Meyenn 2000), this has contributed to development through employment creation, access to services and increased access to information. With such a massive acceptance, mobile technologies create opportunities for Micro and Small Enterprises (MSEs) in rural areas to deploy an eBusiness infrastructure. These technologies also present a unique opportunity for Medium and Small Enterprises (MSEs) to overcome their institutional impediments to Internet access and e-payments by providing new services and technical capabilities such as effective and highly available voice communication, Internet access and e-payments transactions. Availability of these technologies is only an enabling factor. To positively impact an organization’s performance, mobile technologies must appropriately match its eBusiness infrastructure requirements. However, appropriateness alone does not guarantee use. User acceptance is critical to successful implementation of any new technology. This study extends Task-Technology Fit (TTF) theory to incorporate acceptance as a factor that could influence the use of Wireless eBusiness
Differential Impact of HLA-B*44 Allelic Mismaches at Position 156 on Peptide Binding Specificities and T-Cell Diversity

The molecular understanding of how we can mismatch patients and donors and still have successful clinical outcomes will help to guide the future of unrelated bone-marrow transplantation. Single amino acid mismatches at position 156 on the alpha 2 helix of B*44 variants have been described to cause immunological episodes. The magnitude of permissivity between B44/156 variants differs from peptide presentation independent of the peptide loading complex (B*44:28) to influencing clinical episodes (B*44:02 vs. B*44:03). We here investigated if the single exchange of an Asp>Glu as occurring in B*44:35 at residue 156 would force an immune response in vitro. We developed an in vitro system by recombinant co-expression of a single membrane-bound allogeneic HLA class I molecule in donor cells and co-incubating these cells with autologous T-cells. This strategy enables the study of single HLA class I mismatches and excludes the influence of minor antigens. We found these T-cells to be able to differentially discriminate between mismatched B*44 subtypes and their micropolymorphism. To understand how certain pHLA landscapes shaping the alloreactive immune response, we sequenced the individual peptides derived from B*44/156 subtypes using LC-ESI-MS/MS technology. Based on the peptide data we modeled the structure of the B*44:35 variant and can describe the unexpected immunological reaction of the mismatched B*44 subtypes through structural manipulation of the heavy chain. The meticulous characterization of peptide-binding profiles for key alleles, as well as the evaluation of T-cell responses and structural analysis in the context of one-allele mismatches will open the door to a new era in bonemarrow transplantation.
Antenna Mutual Coupling Suppression Over Wideband Using Embedded Periphery Slot for Antenna Arrays

This paper presents a new approach to suppress interference between neighbouring radiating elements resulting from surface wave currents. The proposed technique will enable the realization of low-profile implementation of highly dense antenna configuration necessary in SAR and MIMO communication systems. Unlike other conventional techniques of mutual coupling suppression where a decoupling slab is located between the radiating antennas the proposed technique is simpler and only requires embedding linear slots near the periphery of the patch. Attributes of this technique are (i) significant improvement in the maximum isolation between the adjacent antennas by 26.7 dB in X-band and >15 dB in Ku and K-bands; (ii) reduction in edge-to-edge gap between antennas to 10 mm (0.37 λ); and (iii) improvement in gain by >40% over certain angular directions, which varies between 4.5 dBi and 8.2 dBi. The proposed technique is simple to implement at low cost.
Tachinid Fly (Diptera: Tachinidae) Parasitoids of Danaus plexippus (Lepidoptera: Nymphalidae)

Abstract Extensive rearing of monarch larvae (Danaus plexippus L.) through the citizen science Monarch Larva Monitoring Project (MLMP) revealed that monarchs' primary parasitoids are flies in the family Tachinidae and that these parasitoids result in appreciable larval mortality. We document the tachinid community that attacks monarchs in the United States, evaluate their relative frequency, and examine variation in their specificity, oviposition strategy, and use of host stages. Based on results of rearing >20,000 monarchs by MLMP volunteers, overall parasitism by tachinids across life stages was 9.8% (17% for monarchs collected as fifth instars). We identified the flies that emerged from 466 monarch hosts, and found seven Tachinidae species. In decreasing order of frequency, these included Lespesia archippivora (Riley), Hyphantrophaga virilis (Aldrich & Webber), Compsilura concinnata (Meigen), Leschenaultia n. sp. , Madremyia saundersii (Williston), Lespesia sp. , and Nilea erecta (Coquillett). Lespesia sp. , Leschenaultia n. sp. , and N. erecta had not been previously reported as monarch parasitoids, and Leschenaultia n. sp. is apparently undescribed. We include new state records (Texas and Iowa) for C. concinnata. Lespesia archippivora and C. concinnata were overrepresented as parasitoids of later instars and were absent from monarchs collected as eggs, but H. virilis and Leschenaultia sp. , which lay their eggs on foliage, were reared from caterpillars collected as eggs. To our knowledge, we include the first report of multiparasitism of monarchs, in which more than one parasitoid species emerged from a host. The biology of the tachinid parasitoids we identified and their relationship with monarchs is examined.
of Endangered Great Apes Supplemental Data S 1 Pandemic Human Viruses Cause Decline

Molecular Analysis DNA and RNA were extracted from frozen lung tissue with DNAeasy and RNAeasy tissue kits (QIAGEN, Hilden, Germany) according to the manufacturer’s instructions. cDNA was synthesized by using the Superscript Kit (Invitrogen, Karlsruhe, Germany) and random hexamer primers (TIB Molbiol, Berlin, Germany). Various PCR approaches were applied in order to identify relevant bacteria [S1] and viruses. Samples were screened for influenza virus A-H1, A-H3, B [S2], adenovirus [S3], measles virus [S4], coronaviruses (A.N., unpublished data), picornavirus [S5], parainfluenza virus [S6] (with modified nested primers for Parainfluenza 3: ParaIII-1060: 50-CCCTGGTCC AACAGATGGGT-30 and ParaIII-1150:50-ACACCCAGTTGTGTTGCAGATT-30), RSV [S7], and HMPV [S8]. MassTag PCR [S9, S10], a multiplex assay that uses small molecular tags and mass spectroscopy for detection of multiple PCR products, was also used. Positive samples were further characterized with PCR assays targeting phylogenetically relevant DNA fragments. For HRSV, first and heminested PCRs targeting the hypervariable region of the G protein were performed. The primers specific for subgroup B used for the first PCR were primers GPB and F1. Those used for the heminested PCR were primers nRSBG and F1, as described previously [S7, S11]. To amplify the P Gen of HMPV, the primers MPVP01.6 and MPVM02.4 were used, as described by Mackay [S8]. Amplification was conducted for 5 min at 95 C, followed by 35 cycles of 95 C for 30 s, 54 C for 30 s, and 72 C for 1 min, with a final 10 min of extension at 72 C. PCR products of HMPV and HRSV were purified with the Gel Extraction Spin Kit (Genomed, Loehne, Germany) and then cloned with the Topo TA Cloning Kit (Invitrogen, Karlsruhe, Germany). Colonies were analyzed by colony PCR. Sequencing was performed with the ABI Big Dye Termination Kit (Applied Biosystems, Weiterstadt, Germany).
Placement and Scheduling of Network Traffic on Virtual Network Functions

Hardware MiddleBoxes represent a vital part in today's networks. Despite their important roles, they are accompanied by several problems, namely, their lack of flexibility, high capital and operational expenditures, and power consumption. Network Function Virtualization is one promising solution to address these problems. This trend replaces the MiddleBoxes by software-based entities. Indeed, these Virtual Network Functions promise to alleviate the numerous disadvantages brought by their hardware counterparts. One of these most serious issues is the steadily increasing power consumption. Studies suggest that the Virtual Network Functions will reduce the electricity costs needed to turn on and operate the hardware functions. In order to further optimize the power consumption of the network, an efficient framework, capable of placing and scheduling traffic on these VNFs, is needed. Such a framework allows to optimally map and schedule the flows to be serviced, and place the unused servers in energy saving modes. In this thesis, we assume VNFs are already placed on physical machines. We consider traffic flows with deadlines. We aim at assigning and scheduling flows to VNFs in the most energy efficient manner. We formulate this problem mathematically and, owing to its complexity, present an efficient algorithmic method for solving the problem. We compare our heuristic with two other approaches, one of which aims to minimize the makespan, and the other to minimize number of servers used. We show that our heuristic combines the advantages of both approaches and generates better results by consuming up to 31.3% and 46.1% energy less than other two approaches respectively. Further, we extend the existing work in the literature, and solve the problem of placement of traffic flows on VNFs while taking into account the transmission delay between pairs of VNFs, and the routing of the virtual links on the underlying physical network.
Ergodicity of Dissipative Differential Equations Subject to Random Impulses

Differential equations subject to random impulses are studied. Randomness is introduced both through the time between impulses, which is distributed exponentially, and through the sign of the impulses, which are fixed in amplitude and orientation. Such models are particular instances of piecewise deterministic Markov processes and they arise naturally in the study of a number of physical phenomena, particularly impacting systems. The underlying deterministic semigroup is assumed to be dissipative and a general theorem which establishes the existence of invariant measures for the randomly forced problem is proved. Further structure is then added to the deterministic semigroup, which enables the proof of ergodic theorems. Characteristic functions are used for the case when the deterministic component forms a damped linear problem and irreducibility measures are employed for the study of a randomly forced damped double-well nonlinear oscillator with a gradient structure.
Characterization of Organic Matter under Different Pedoenvironments in the Viruá National Park, in Northern Amazon

Soil organic matter (SOM) fractions result from a variety of environmental processes, which affect incorporation and production rates, decomposition, alteration, and/or mineralization of organic matter. The aim of this study was to characterize SOM under the environments of rain forest, wooded campinarana (grasslands), arboreal-shrubby campinarana, grassy-woody campinarana, and pioneer plants of the Virua National Park, in the north of the Brazilian Amazon. After chemical and physical characterization and soil classification, total organic carbon (TOC), total N, microbial activity, organic C from fulvic acid fractions (FA), humic acid (HA), and humin (Hu) were determined at two depths (0.00-0.15 and 0.15-0.30 m). The TOC was lower in the grassy-woody campinarana, arboreal-shrubby campinarana, and pioneer formation areas than in the rain forest. Higher values of microbial activity were related to forest ecosystems in soils without physical or water restrictions and with better fertility compared to the other areas. The Hu predominated in all vegetation types studied, especially in the surface layer, because of the more soluble nature of HA and FA; and the higher values of HA/FA ratios in wooded campinaranas indicate that these environments contribute to higher losses of humic substances through fulvic acid forms, due to better drainage conditions.
Specification Curve: Descriptive and Inferential Statistics on All Reasonable Specifications

Empirical results often hinge on data analytic decisions that are simultaneously defensible, arbitrary, and motivated. To mitigate this problem we introduce Specification-Curve Analysis, which consists of three steps: (i) identifying the set of theoretically justified, statistically valid, and non-redundant analytic specifications, (ii) displaying alternative results graphically, allowing the identification of decisions producing different results, and (iii) conducting statistical tests to determine whether as a whole results are inconsistent with the null hypothesis. We illustrate its use by applying it to three published findings. One proves robust, one weak, one not robust at all.
Automated Scoring of an Interactive Geometry Item: A Proof-of-Concept

An online interactive geometry item was developed to explore students’ abilities to create prototypical and “tilted” rectangles out of line segments. The item was administered to 1,002 students. The responses to the item were hand-coded as correct, incorrect, or incorrect with possible evidence of a misconception. A variation of the nearest neighbor algorithm was used to automatically predict one of these categories for each of the student responses. The predicted category was compared to the hand-coded category. The algorithm accurately predicted the category for 94.6% of responses.
Marine Biofouling Potential on Reverse Osmosis Desalination Membrane and Other Substrata Corresponding to in situ Microbial and Physicochemical Characterization of Seawater

In situ investigation was designed for following up the biofouling community formed on the different substrata representative of the desalination unit components including Teflon, Glass, Stainless steel and Reverse Osmosis desalination membrane (RO desalination membrane), submerged in the seawater of the Eastern Harbor, Alexandria, Egypt. The area of study was physico-chemically and microbially characterized along 84 days, the time of the experiment. Some physico-chemical parameters such as Temperature, pH, dissolved oxygen, salinity, and nutrients (ammonia, nitrite, nitrate, phosphate, and silicate) were estimated. For in situ microbial characterization of seawater, the total heterotrophic bacteria and total marine fungi, in addition to several bacterial groups were counted. Data indicated that the total count of heterotrophic bacteria increased linearly with time until it reached the peak after 42 days of submerging coupons (4x106 CFU/ml), then it decreased with the time until the end of submerging trail. The count of common pathogenic bacteria Staphylococcus sp. , Vibrio sp. And Aeromonas sp. was in same trend but the counts of Staphylococcus sp. were more than of the others. On the other side, Salmonella/Shigella group was not detected in samples at all. The fecal indicator bacteria exhibited moderate counts, while the count of total marine fungi in the seawater samples showed low counts along the period of submerging coupons. Regarding the marine fouling, a total of 36 coupons were examined along 84 days of submerging in the seawater. Throughout the study 21 species of marine macro-fouling were recorded in addition to the very thin layer of blue-green algae. These belonged to different groups as follows: Macroalgae (2 species), Hydriods (1 species), Polychaets (5 species; 3 sedentarian and 2 errantias), Cirripeds (4 species), amphipods (4 species), Taniads (1 species), bryozoan (2 species), and tunicates (2 species). There are clear dominances by two sessile species. These are the polychaete (tube worm); Hydroideselegans and the barnacle; Balanusamphitrite. In average, they constituted about 50% and 29% of total fouling abundance, respectively. Across the different substrates, the average total abundance and biomass of the developing fouling community was comparable during different intervals of immersion except for the glass which showed the lowest values. Responsible factors for these variations are discussed.
Anticancer and apoptosis-inducing activities of microbial metabolites

The problems of systemic toxicity and drug resistance in cancer chemotherapy urge the continuing discovery of new anticancer agents. We explored the specific anticancer activity from microbial metabolites to find new lead compound. 394 microbial extracts were evaluated on anti-proliferative activity against 4 cancer cell lines using MTT assay. Of these, 20 samples showed varying degree of cytotoxicity but specifically to the cancer cell lines since the growth of normal cells was not significantly inhibited by 1 mg/ml of each cell extracts. The 4 most potent extracts exhibited strongest growth inhibition to each cancer cell type were selected for further studied. Cell morphological changes such as cell shrinkage, lose of surface contact and blebbing were observed in all treated cancer cells. DNA-binding dye staining demonstrated nuclear condensation and fragmentation. Chromosomal DNA cleavage detected as DNA ladder pattern by gel electrophoresis including activation of cellular caspase-3 activity, a hallmark of apoptosis, were observed in all treated cancer cell lines. These characteristics suggested the mechanism of apoptosis cell death induced by the extracts. No growth inhibition and apoptosis characteristic were detected in normal cells even at high concentration used suggesting the selective cytotoxicity and potential candidates to develop as anticancer agents.