Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimized Implementation of the Elliptic Curve Factorization Method on a Highly Parallelized Hardware Cluster

In this thesis we present a highly efficient, parallel implementation of the elliptic curve method (ECM) on reconfigurable hardware in order to support the general number field sieve algorithm (GNFS). The GNFS is the most effective algorithm to factor large integers. It can be used to attack the RSA cryptosystem by factoring the composite RSA modulus N = p · q. During the sieving step, a large amount of mid-sized integers have to be factored. We can use the ECM to increase the speed of this step. To provide fast modular arithmetic units, we exploit the digital signal processing elements on a Virtex-4 FPGA and increase the speed of the underlying operations compared to other FPGA implementations. We present an optimized implementation on a Virtex-4 SX35 FPGA, running 24 parallel ECM computations of phase 1 and phase 2 at 200 MHz. We propose an architecture, which can be adapted to factor 66 to 236 bit integers. The necessary hardware changes are negligible, as only the instruction sequence has to be recomputed. Our results show an improvement by more than 20% compared to all previous publications on FPGAs (which implement or estimate the second phase) both on throughput as well as cost-effectiveness. Our comparison with a recent implementation of the ECM on graphic cards indicate that even though FPGAs do not have the computational power of modern GPUs, FPGAs are more power-effective.
Using corn gluten feed in post-partum diets of young beef cows to optimize reproductive performance

Abstract Forty-eight primiparous and diparous Angus-Simmental cows were fed 1 of 3 diets; 1) total mixed ration (TMR) based of corn silage and corn stalks (CON), 2) TMR with 3.3 kg/d DM of corn gluten feed (CGF; MID), or 3) TMR with 6.7 kg/d DM of CGF (HIGH). From 11 ± 5 days post-partum (DPP) to 105 ± 5 DPP, all diets were formulated to be isocaloric for a post-partum ADG targeted at 0.22 kg, but CP exceeded requirements in both CGF diets. Blood samples were collected from cows starting at trial initiation until estrous synchronization for determination of plasma progesterone concentration (7 d intervals), as an indicator of resumption of cyclicity, as well as for plasma urea nitrogen (PUN; 21 d intervals). Milk production was assessed at 62 ± 5 DPP via a weigh-suckle-weigh procedure, and milk samples were collected at 64 ± 5 DPP for composition analysis. A 5 d Co-Synch + Control Internal Drug Release (CIDR) protocol was used and cows were bred by timed artificial insemination (TAI). Trans-rectal ultrasonography was used for the evaluation of the dominant follicle at TAI, as well as pregnancy diagnosis. Nineteen days post-TAI, cow and calf pairs were managed as a single group until weaning (205 ± 5 DPP) and exposed to natural mating for a total of a 60 d breeding season. Dam ADG was not significantly different among treatments (P = 0.849), but, DMI decreased with increasing CGF in the diet (P = 0.049). There were no differences in final BW (P = 0.779), however, final BCS was lower in the HIGH treatment when compared to the MID (P = 0.042). Milk production (P = 0.457), as well as, milk components (P ≥ 0.188) were not different, with the exception of milk fat, which tended to be greater in the HIGH treatment (P = 0.059) when compared to the MID. A treatment by week interaction (P < 0.0001) was found for PUN concentrations. Concentrations were greater in the HIGH treatment compared to the MID treatment at 63, 84, and 105 d, and greater than the CON treatment at all time points except d-42. There were no differences in resumption of cyclicity (P = 0.419), dominant follicle (P = 0.648), or TAI conception rates (P = 0.761). However, season long pregnancy rates were significantly greater in the CGF treatments when compared to the CON (P = 0.009). In summary, feeding high or intermediate amounts of CGF neither has a positive nor negative effect on TAI conception rates of beef cows, however, it positively affected season long pregnancy.
Validation of the MINI (DSM IV) Tool for the Assessment of Alcohol Dependence among Young People in Northern Tanzania Using the Alcohol Biomarker Phosphatidylethanol (PEth)

The alcohol dependence section of the Mini International Neuropsychiatric Interview questionnaire (MINI) has not been evaluated in young Africans. We applied the MINI in a cross-sectional study of 202 alcohol users from northern-Tanzania, aged 18–24 years (103 male casual workers and 99 students), and validated it against phophatidylethanol (PEth) at a cut-off suggesting heavy chronic alcohol use (≥0.30 µmol/L). Blood was assayed for PEth (16:0/18:1-subform) by liquid chromatography-tandem mass spectrometry. The MINI dependence criteria (≥3 positive responses) were met by 39% participants although their PEth levels were low. Contrary, many young people with high PEth levels were not classified as dependent. The sensitivity of the MINI ranged from 0% to 69% (female students and male workers, respectively) and specificity from 52% to 85% (workers and female students, respectively). The highest AUROC (0.68) occurred with a cut-off of ≥4 positive responses. A modified MINI with three affirmative responses to five questions increased specificity to 92%–97%; however, sensitivity remained low. The performance of the MINI in detecting dependence among young people from northern-Tanzania is unsatisfactory. Specificity was improved using a modified version but sensitivity remained low. An accurate tool for the diagnosis of alcohol dependence is needed for epidemiological and clinical purposes.
Capo: a software-hardware interface for practical deterministic multiprocessor replay

While deterministic replay of parallel programs is a powerful technique, current proposals have shortcomings. Specifically, software-based replay systems have high overheads on multiprocessors, while hardware-based proposals focus only on basic hardware-level mechanisms, ignoring the overall replay system. To be practical, hardware-based replay systems need to support an environment with multiple parallel jobs running concurrently -- some being recorded, others being replayed and even others running without recording or replay. Moreover, they need to manage limited-size log buffers. This paper addresses these shortcomings by introducing, for the first time, a set of abstractions and a software-hardware interface for practical hardware-assisted replay of multiprocessor systems. The approach, called Capo, introduces the novel abstraction of the Replay Sphere to separate the responsibilities of the hardware and software components of the replay system. In this paper, we also design and build CapoOne, a prototype of a deterministic multiprocessor replay system that implements Capo using Linux and simulated DeLorean hardware. Our evaluation of 4-processor executions shows that CapoOne largely records with the efficiency of hardware-based schemes and the flexibility of software-based schemes.
Efficient Mean Shift Clustering Using Exponential Integral Kernels

— This paper presents a highly efficient algorithm for detecting and tracking humans and objects in video surveillance sequences. Mean shift clustering is applied on background-differenced image sequences. For efficiency, all calculations are performed on integral images. Novel corresponding exponential integral kernels are introduced to allow the application of non-uniform kernels for clustering, which dramatically increases robustness without giving up the efficiency of the integral data structures. Experimental results demonstrating the power of this approach are presented.
Noise Reduction for Magnetic Resonance Images via Adaptive Multiscale Products Thresholding

Edge-preserving denoising is of great interest in medical image processing. This paper presents a wavelet-based multiscale products thresholding scheme for noise suppression of magnetic resonance images. A Canny edge detector-like dyadic wavelet transform is employed. This results in the significant features in images evolving with high magnitude across wavelet scales, while noise decays rapidly. To exploit the wavelet interscale dependencies we multiply the adjacent wavelet subbands to enhance edge structures while weakening noise. In the multiscale products, edges can be effectively distinguished from noise. Thereafter, an adaptive threshold is calculated and imposed on the products, instead of on the wavelet coefficients, to identify important features. Experiments show that the proposed scheme better suppresses noise and preserves edges than other wavelet-thresholding denoising methods.
Maximum a-posteriori probability pitch tracking in noisy environments using harmonic model

Modern speech processing applications require operation on signal of interest that is contaminated by high level of noise. This situation calls for a greater robustness in estimation of the speech parameters, a task which is hard to achieve using standard speech models. In this paper, we present an optimal estimation procedure for sound signals (such as speech) that are modeled by harmonic sources. The harmonic model achieves more robust and accurate estimation of voiced speech parameters. Using maximum a posteriori probability framework, successful tracking of pitch parameters is possible in ultra low signal to noise conditions (as low as -15 dB). The performance of the method is evaluated using the Keele pitch detection database with realistic background noise. The results show best performance in comparison to other state-of-the-art pitch detectors. Application of the proposed algorithm in a simple speaker identification system shows significant improvement in the performance.
Functional consequences of interleukin 2 receptor expression on resting human lymphocytes. Identification of a novel natural killer cell subset with high affinity receptors

In this study, we have used radiolabeled IL-2 binding assays, Northern blot analysis, immunofluorescent flow cytometry and cell sorting, as well as proliferation and cytotoxicity assays to perform an extensive phenotypic and functional characterization of the IL-2 receptor in normal resting human peripheral blood lymphocytes. Our results indicate that almost all T cells (greater than 98%) express neither the high affinity IL-2 receptor nor the functional intermediate affinity p75 chain of the IL-2 receptor without prior activation. In contrast, most NK cells constitutively express the isolated intermediate affinity p75 IL-2 receptor. In addition, a subpopulation of NK cells, distinguished by high density expression of the NKH1 antigen, constitutively express the high affinity IL-2 receptor, in addition to an excess of the isolated intermediate affinity p75 IL-2 receptor. These NKH1bright+ cells exhibit a brisk proliferative response to IL-2, similar to that seen with antigen-activated T cells, yet do so in the absence of any known antigenic stimuli. No other resting peripheral blood lymphocyte population, including CD4+, CD8+, and CD20 cells, exhibits this property. The intermediate affinity p75 IL-2 receptor, as it exists in its isolated form on resting NK cells, does not transduce a growth signal equivalent to that seen in NK cells expressing the high affinity IL-2 receptor, despite doses of IL-2 that are known to fully saturate the isolated p75 chain. This strongly suggests that additional structural or functional components are involved in generating the proliferative response following the binding of IL-2 to the high affinity heterodimeric form of the IL-2 receptor. The constitutive expression of this functional high affinity IL-2 receptor on a small population of resting NK cells provides further evidence in support of a role for these cells in the host's early defense against viral infection or malignant transformation, before the more delayed but specific T cell response.
University of Birmingham A novel method for prokaryotic promoter prediction based on DNA stability

Background: In the post-genomic era, correct gene prediction has become one of the biggest challenges in genome annotation. Improved promoter prediction methods can be one step towards developing more reliable ab initio gene prediction methods. This work presents a novel prokaryotic promoter prediction method based on DNA stability. Results: The promoter region is less stable and hence more prone to melting as compared to other genomic regions. Our analysis shows that a method of promoter prediction based on the differences in the stability of DNA sequences in the promoter and non-promoter region works much better compared to existing prokaryotic promoter prediction programs, which are based on sequence motif searches. At present the method works optimally for genomes such as that of Escherichia coli , which have near 50 % G+C composition and also performs satisfactorily in case of other prokaryotic promoters. Conclusions: Our analysis clearly shows that the change in stability of DNA seems to provide a much better clue than usual sequence motifs, such as Pribnow box and -35 sequence, for differentiating promoter region from non-promoter regions. To a certain extent, it is more general and is likely to be applicable across organisms. Hence incorporation of such features in addition to the signature motifs can greatly improve the presently available promoter prediction programs.
Climate‐driven increases in storm frequency simplify kelp forest food webs

Climate models predict a dramatic increase in the annual frequency and severity of extreme weather events during the next century. Here we show that increases in the annual frequency of severe storms lead to a decrease in the diversity and complexity of food webs of giant kelp forests, one of the most productive habitats on Earth. We demonstrate this by linking natural variation in storms with measured changes in kelp forest food web structure in the Santa Barbara Channel using structural equation modeling (SEM). We then match predictions from statistical models to results from a multiyear kelp removal experiment designed to simulate frequent large storms. Both SEM models and experiments agree: if large storms remain at their current annual frequency (roughly one major kelp‐removing storm every 3.5 years), periodic storms help maintain the complexity of kelp forest food webs. However, if large storms increase in annual frequency and begin to occur year after year, kelp forest food webs become less diverse and complex as species go locally extinct. The loss of complexity occurs primarily due to decreases in the diversity and complexity of higher trophic levels. Our findings demonstrate that shifts in climate‐driven disturbances that affect foundation species are likely to have impacts that cascade through entire ecosystems.
Assessment of students knowledge and perceptions about biodiversity and conservation method in Harari regional State, eastern Ethiopia

The term biodiversity refers the number and variability of living organisms on the plant and it is the heart of sustainable development and the life insurance in itself. The main objective of this study was to assess students’ level of knowledge and perception about biodiversity conservation techniques, hence strengthening and developing students’ level of knowledge and perception towards biodiversity conservation has a great role to protect the variety of all species in the ecosystem. The study has employed both qualitative and quantitative methods such as individual interview, FGD and structured questionnaire. A total 360 students from two target groups (grade 10 and 12) selected from 6 secondary and preparatory schools were involved. The results showed that students’ level of knowledge and perception towards biodiversity conservation was varied. Accordingly, above 50% and 70% of the students of grade 12 were found above mastery level in their knowledge and had shown favorable perception respectively regarding biodiversity conservation whereas students from grade 10 above 50% were found below mastery level regarding their knowledge and above 50% of the students also had shown favorable perception about conservation of biodiversity resource. This indicated that the students were not more awareness about biodiversity and conservation methods due to different factors like teaching learning of biodiversity conservation was found ineffective due to lack of facilities, lack of effective implementation of the stated methodology in their text book and large class size. Thus, it can be concluded that the students has not get the expected change in knowledge and perception among students about conservation of biodiversity resources particularly in grade 10 with in the school. Therefore, fulfilling of the necessary facilities, awareness creation on the concerning body and implementing effectively the teaching methods of biodiversity conservation that included in their text book such as field exposure, group discussion active classroom session and continues assessment in the study area is highly recommended.
Distinct catalytic roles of the SecYE, SecG and SecDFyajC subunits of preprotein translocase holoenzyme

Escherichia coli preprotein translocase contains a membrane‐embedded trimeric complex of SecY, SecE and SecG (SecYEG) and the peripheral SecA protein. SecYE is the conserved functional ‘core’ of the SecYEG complex. Although sufficient to provide sites for high‐affinity binding and membrane insertion of SecA, and for its activation as a preprotein‐dependent ATPase, SecYE has only very low capacity to support translocation. The proteins encoded by the secD operon—SecD, SecF and YajC—also form an integral membrane heterotrimeric complex (SecDFyajC). Physical and functional studies show that these two trimeric complexes are associated to form SecYEGDFyajC, the hexameric integral membrane domain of the preprotein translocase ‘holoenzyme’. Either SecG or SecDFyajC can support the translocation activity of SecYE by facilitating the ATP‐driven cycle of SecA membrane insertion and de‐insertion at different stages of the translocation reaction. Our findings show that each of the prokaryote‐specific subunits (SecA, SecG and SecDFyajC) function together to promote preprotein movement at the SecYE core of the translocase.
An Empirical Study into Social Success Factors for Agile Software Development

Though many warn that Agile at larger scale is problematic or at least more challenging than in smaller projects, Agile software development seems to become the norm, also for large and complex projects. Based on literature and qualitative interviews, we constructed a conceptual model of social factors that may be of influence on the success of software development projects in general, and of Agile projects in particular. We also included project size as a candidate success factor. We tested the model on a set of 40 projects from 19 Dutch organizations, comprising a total of 141 project members, Scrum Masters and product owners. We found that project size does not determine Agile project success. Rather, value congruence, degree of adoption of Agile practices, and transformational leadership proved to be the most important predictors for Agile project success.
Positive-unlabeled ensemble learning for kinase substrate prediction from dynamic phosphoproteomics data

MOTIVATION Protein phosphorylation is a post-translational modification that underlines various aspects of cellular signaling. A key step to reconstructing signaling networks involves identification of the set of all kinases and their substrates. Experimental characterization of kinase substrates is both expensive and time-consuming. To expedite the discovery of novel substrates, computational approaches based on kinase recognition sequence (motifs) from known substrates, protein structure, interaction and co-localization have been proposed. However, rarely do these methods take into account the dynamic responses of signaling cascades measured from in vivo cellular systems. Given that recent advances in mass spectrometry-based technologies make it possible to quantify phosphorylation on a proteome-wide scale, computational approaches that can integrate static features with dynamic phosphoproteome data would greatly facilitate the prediction of biologically relevant kinase-specific substrates. RESULTS Here, we propose a positive-unlabeled ensemble learning approach that integrates dynamic phosphoproteomics data with static kinase recognition motifs to predict novel substrates for kinases of interest. We extended a positive-unlabeled learning technique for an ensemble model, which significantly improves prediction sensitivity on novel substrates of kinases while retaining high specificity. We evaluated the performance of the proposed model using simulation studies and subsequently applied it to predict novel substrates of key kinases relevant to insulin signaling. Our analyses show that static sequence motifs and dynamic phosphoproteomics data are complementary and that the proposed integrated model performs better than methods relying only on static information for accurate prediction of kinase-specific substrates. AVAILABILITY AND IMPLEMENTATION Executable GUI tool, source code and documentation are freely available at https://github.com/PengyiYang/KSP-PUEL. CONTACT pengyi.yang@nih.gov or jothi@mail.nih.gov SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Association between hand-grip strength and depressive symptoms: Locomotive Syndrome and Health Outcomes in Aizu Cohort Study (LOHAS).

BACKGROUND no study has examined the longitudinal association between hand-grip strength and mental health, such as depressive symptoms. OBJECTIVE we investigated the relationship between baseline hand-grip strength and the risk of depressive symptoms. DESIGN a prospective cohort study. SETTING AND SUBJECTS a prospective cohort study with a 1-year follow-up was conducted using 4,314 subjects from community-dwelling individuals aged 40-79 years in two Japanese municipalities, based on the Locomotive Syndrome and Health Outcomes in Aizu Cohort Study (LOHAS, 2008-10). METHODS we assessed baseline hand-grip strength standardised using national representative data classified by age and gender, and depressive symptoms at baseline and after the follow-up using the five-item version of the Mental Health Inventory (MHI-5). RESULTS the 4,314 subjects had a mean age of 66.3 years, 58.5% were women, and mean unadjusted hand-grip strength was 29.8 kg. Multivariable random-effect logistic regression analysis revealed that subjects with lower hand-grip strength (per 1SD decrease) had higher odds of having depressive symptoms at baseline [adjusted odds ratio (AOR) 1.15, 95% confidence interval (CI) 1.06-1.24; P = 0.001]. Further, lower hand-grip strength (per 1SD decrease) was associated with the longitudinal development of depressive symptoms after 1 year (AOR 1.13, 95% CI 1.01-1.27; P = 0.036). CONCLUSIONS using a large population-based sample, our results suggest that lower hand-grip strength, standardised using age and gender, is both cross-sectionally and longitudinally associated with depressive symptoms.