Miracle-dz/UniFAR-FTUs huggingface dataset:
Nature and Structure of the Climax

NATURE OF THE CLIMAX . 254 Unity of the climax . 254 Stabilisation and change . 255 Origin and relationship . 257 Tests of a climax . 257 CLIMAX AND PROCLIMAX . 261 Essential relations. 261 Proclimaxes 262 Subelimax . 262 Disclimax 265 Preclimax and postclimax. 266 Preclimax 267 Postclimax . 269 STRUCTURE OF THE CLIMAX . 270 Community functions. 270 Roles of the constituent species: dominants 270 Influents . 271 Climax and seral units . 271 Climax units . 272 Association . 273 Consociation . 274 Faciation . 274 Lociation . 275 Society . 275 Sociation . 276 Lamiation . 277 Sation . 277 Clan . 278 Seral units . 278 Serule . 280
A Comparison of Fathers' and Mothers' Speech with Their Young Children.

: The verbal interaction of 12 mothers and 12 fathers with their 19-month-old girls and boys in 2 situations was assessed. In 1 situation, all 3 family members were together, while in the other, each parent was alone with the child. Analyses indicated that when all 3 family members were together, fathers spoke less and took fewer conversational turns than mothers. Other than these significant differences, fathers' speech to their children was not different from mothers' speech on a range of quantitative and qualitative measures.
Tooth form and diet in ateline and alouattine primates; reflections on the comparative method

By identifying consistent relationships between mor­ phology and ecology across taxa, the comparative method allows the testin~ of ideas about adaptation and permits the reconstruction of behavIOr in extinct forms. The association between dental morphology and dietary adaptation is explored for ateline and alouattine ~rimates. Using allometrIC techniques and a "criterion of subtraction' reveals that folivores (Alouatta, Brachyteles) have relatively small lower incisors and relatively well-developed molar shearing crests compared to frugi­ vores (Ateles, Lagothrix). The development of molar shear crests in the fossil alouattines of the genus Stirtonia is indicative of diets nearly as folivorous as in Alouatta. The existence of multiple adaptive solutions to a single selective pressure does not preclude usin~ the comparative method for predic­ tive purposes as long as the goal IS to infer behavior from morphology and not the reverse. Similarly, nonadaptive convergence does not invalidate the entire comparative method but only means that not all hypothesized relationships between morphology and behavior will have predictive power. Comparative hypotheses mar be tested at any taxonomic level for which there is measurable variatIOn in the traits to be examined. However, considering only independent evolutionary occurrences-rather than individual taxa-disregards trait mainte­ nance as a valid trial of a comparative hypothesis.
Total Phenolic Content and Associated Phenotypic Traits in a Diverse Collection of Snap Bean Cultivars

ABSTRACT. Phytochemicals such as phenolic compounds in snap bean (Phaseolus vulgaris) have potential human health benefits. The objectives of this research were to determine the variation in total phenolic content (TPC) measured as gallic acid equivalents (GAEs)—expressed on a fresh weight (FW) basis throughout this study—among a diverse collection of both indeterminate climbing (pole) and determinate (bush) bean cultivars (n = 149) using the Folin– Ciocalteu assay. We also evaluated associations between TPC and phenotypic traits and estimated genotype by environment (G · E) interactions in a subset of the cultivars. The TPC had greater than a 4-fold difference among cultivars and ranged from 0.29 to 1.31 mg g GAE (mean = 0.49 mg g GAE). Cultivars were classified into categories of high (‡1.00mg g GAE), intermediate (>0.64 to <1.00mg g GAE), and low (<0.55mg g GAE) TPC. Eighty-four percent, 10%, and 6% of the cultivars fell into the low, intermediate, and high categories, respectively. The pole type cultivars had higher TPC (mean = 0.86 mg g GAE) when compared with the bush cultivars (mean = 0.47 mg g GAE). Correlations were observed between TPC and both flower and pod pigmentation. G · E interactions did not occur among pole type cultivars for TPC during 2 years of production, but a significant G · E interaction was observed among bush cultivars. The results demonstrate a wide diversity in snap bean cultivars for TPC, and the pole beans averaged higher TPC than bush bean cultivars. This information should be useful to identify high TPC snap bean cultivars.
Taking Management Digital: Lessons from the Development of an Innovative Management Information System for Small Businesses in Ethiopia

In many aid projects, monitoring and evaluation is a static exercise driven by donor reporting requirements. After project closure, there are seldom sustainable benefits of the monitoring and evaluation system. This paper examines how monitoring and evaluation can be transformed into a dynamic tool for effective project management, with benefits carrying over beyond the typical project lifecycle. The paper assesses an innovative, digital management information system developed under the Women Entrepreneurship Development Project, a Government of Ethiopia initiative financed by a World Bank International Development Association loan and grant funding from Global Affairs Canada. The paper examines the context of the development of the management information system, its effectiveness, and its potential for sustainability. Ethiopia is among the poorest countries in the world, and government administration units involved in administering projects often face funding and resource shortfalls. The paper demonstrates how effective and sustainable monitoring and evaluation systems can be developed even in challenging contexts such as these, by focusing on simple technical solutions that can be maintained and refined locally, ensuring low development and maintenance costs compatible with government monitoring and evaluation budgets, and linking project-level monitoring and evaluation to broader government operations.
SYMPOSIUM: OPTIMIZING ENERGY NUTRITION FOR REPRODUCING DAIRY COWS Influence of Supplemental Fats on Reproductive Tissues and Performance of Lactating Cows 1

Fat supplementation (about 3% of dietary dry matter) has often positively influenced the reproductive status of the dairy cow, including increased size of the ovulatory follicle, increased numbers of ovarian follicles, increased plasma concentration of progesterone, reduced secretion of prostaglandin metabolite, increased lifespan of the corpus luteum, and improved fertility. Supplemental fat may allay partially negative energy status during the early postpartum period, yet often the positive reproductive influence of supplemental fat has been independent of the energy status of the cow. The fatty acid profile of supplemental fats is influential to their impact. Linoleic acid and eicosapentaenoic acid (found in fish meal) are proven inhibitors of cyclooxygenase in endometrial tissue of dairy cows. As a result, endometrial secretion of PGFa can be suppressed, thus potentially preventing early embryonic death. This process may be aided by the effect fat has in suppressing estradiol17b secretion, thus reducing uterine PGF2a secretion and decreasing the sensitivity of the corpus luteum to PGF2a. Targeting of dietary fatty acids toward ovarian and uterine function may enhance efficiency of reproductive management and fertility.
107 Evaluating the inclusion level of medium chain fatty acids to reduce the risk of PEDV in feed and spray-dried animal plasma.

Citation: Cochrane, R. A. , Saensukjaroenphon, M. , Dritz, S. S. , Woodworth, J. C. , Huss, A. R. , Stark, C. R. , . Jones, C. K. (2016). Evaluating the inclusion level of medium chain fatty acids to reduce the risk of PEDV in feed and spray-dried animal plasma. Journal of Animal Science, 94, 50-50. doi:10.2527/msasas2016-107
A mechanical and enzymatic approach to recovery of ovarian follicular oocytes in rabbits.

In order to investigate the morphology of oocytes which were recovered from ovarian follicles at several developmental stages and to examine the in vitro maturity of recovered oocytes, rabbit ovarian oocytes were recovered by mincing the ovary with a pair of razors and/or cutting isolated follicles. Twenty four point six oocytes per ovary were recovered by mincing the ovary with a pair of razors, and 19.9% of them were surrounded by a thick layer of cumulus cells. The mass of ovarian tissue remnant was digested by a collagenase solution to isolate ovarian follicles at several developmental stages. A great number of ovarian follicles (304.9±114.0 per ovary) could be collected by enzymatic isolation, however, it is difficult to isolate follicles over 700μm in diameter. The oocytes from antral follicles which were isolated enzymatically ( ? 300 Am in diame-ter) were obtained by cutting with a pair of razors, but oocytes could not be recovered from preantral follicles by the same procedure. Some oocytes obtained by cutting follicles were cultured for 20 hr in TCM 199 supplemented with 15% FBS for in vitro matu-ration. Oocytes with a thick layer of cumulus cells were obtained only from follicles over 700 Am in diameter. They emitted the first polar body in vitro at a higher rate as compared with the other types of oocytes, which were surrounded by a thin or partial cumulus cell layer or had no cumulus cells at all. All types of oocytes resumed meiosis in vitro, although high percentages of the oocytes from the smaller follicles and/or in the cumulus free oocytes degenerated. These results suggest that a combination of mincing ovaries and cutting follicles which were isolated enzymatically or mechanically is useful for recovering a great number of oocytes. However, in vitro maturity of those oocytes depends on the follicular size and/or cumulus cells' adhesion to the oocytes.
Revealing the biotechnological potential of Delftia sp. JD2 by a genomic approach

Delftia sp. JD2 is a chromium-resistant bacterium that reduces Cr(VI) to Cr(III), accumulates Pb(II), produces the phytohormone indole-3-acetic acid and siderophores, and increases the plant growth performance of rhizobia in co-inoculation experiments. We aimed to analyze the biotechnological potential of JD2 using a genomic approach. JD2 has a genome of 6.76Mb, with 6,051 predicted protein coding sequences and 93 RNA genes (tRNA and rRNA). The indole-acetamide pathway was identified as responsible for the synthesis of indole-3-acetic acid. The genetic information involved in chromium resistance (the gene cluster, chrBACF, ) was found. At least 40 putative genes encoding for TonB-dependent receptors, probably involved in the utilization of siderophores and biopolymers, and genes for the synthesis, maturation, exportation and uptake of pyoverdine, and acquisition of Fe-pyochelin and Fe-enterobactin were also identified. The information also suggests that JD2 produce polyhydroxybutyrate, a carbon reserve polymer commonly used for manufacturing petrochemical free bioplastics. In addition, JD2 may degrade lignin-derived aromatic compounds to 2-pyrone-4,6-dicarboxylate, a molecule used in the bio-based polymer industry. Finally, a comparative genomic analysis of JD2, Delftia sp. Cs1-4 and Delftia acidovorans SPH-1 is also discussed. The present work provides insights into the physiology and genetics of a microorganism with many potential uses in biotechnology.
PLANEJAMENTO ESPACIAL DA COLHEITA CONSIDERANDO ÁREAS MÁXIMAS OPERACIONAIS

Um dos maiores desafios com que se deparam os gestores na realizacao do planejamento da producao florestal se refere as questoes logisticas das operacoes de colheita. O planejamento operacional da colheita florestal deve ser realizado de forma a conciliar as questoes economicas e ambientais, buscando aumentar a eficiencia e mitigar danos relacionados a abertura da cobertura florestal. A inclusao de relacoes espaciais no planejamento da colheita florestal usualmente e realizada por meio de restricoes de adjacencia. Para resolver este tipo de problema os principais enfoques utilizados sao a abordagem URM (Unit Restriction Model) e a abordagem ARM (Area Restriction Model). Neste contexto, o objetivo do estudo foi realizar o planejamento florestal otimizado dos 236 talhoes de uma floresta composta por Pinus taeda e Eucalyptus sp. , incorporando ao modelo restricoes classicas como area disponivel e equilibrio, entre outras, e as restricoes de adjacencia do tipo URM e ARM, avaliando seu efeito no resultado da otimizacao. Com os resultados da otimizacao e possivel concluir que abordagens ARM e URM sao alternativas viaveis para tratar de problemas de agendamento da colheita florestal, sendo que para a area em questao a abordagem ARM e a mais adequada, devido a possibilidade de obter maiores retornos economicos, respeitando areas limites de colheita.
Spectrum of deep learning algorithms in drug discovery

Deep learning (DL) algorithms are a subset of machine learning algorithms with the aim of modeling complex mapping between a set of elements and their classes. In parallel to the advance in revealing the molecular bases of diseases, a notable innovation has been undertaken to apply DL in data/libraries management, reaction optimizations, differentiating uncertainties, molecule constructions, creating metrics from qualitative results, and prediction of structures or interactions. From source identification to lead discovery and medicinal chemistry of the drug candidate, drug delivery, and modification, the challenges can be subjected to artificial intelligence algorithms to aid in the generation and interpretation of data. Discovery and design approach, both demand automation, large data management and data fusion by the advance in high‐throughput mode. The application of DL can accelerate the exploration of drug mechanisms, finding novel indications for existing drugs (drug repositioning), drug development, and preclinical and clinical studies. The impact of DL in the workflow of drug discovery, design, and their complementary tools are highlighted in this review. Additionally, the type of DL algorithms used for this purpose, and their pros and cons along with the dominant directions of future research are presented.
A natural language processing approach based on embedding deep learning from heterogeneous compounds for quantitative structure–activity relationship modeling

Over the past decade, rapid development in biological and chemical technologies such as high‐throughput screening, parallel synthesis, has been significantly increased the amount of data, which requires the creation and the integration of new analytical methods, especially deep learning models. Recently, there is an increasing interest in deep learning utilization in computer‐aided drug discovery due to its exceptional successful application in many fields. The present work proposed a natural language processing approach, based on embedding deep neural networks. Our method aims to transform the Simplified Molecular Input Line Entry System format into word embedding vectors to represent the semantics of compounds. These vectors are fed into supervised machine learning algorithms such as convolutional long short‐term memory neural network, support vector machine, and random forest to build up quantitative structure–activity relationship models on toxicity data sets. The obtained results on toxicity data to the ciliate Tetrahymena pyriformis (IGC50), and acute toxicity rat data expressed as median lethal dose of treated rats (LD50) show that our approach can eventually be used to predict the activities of chemical compounds efficiently. All material used in this study is available online through the GitHub portal (https://github.com/BoukeliaAbdelbasset/NLPDeepQSAR.git).
Blurring the Lines between Physical and Digital Spaces: Business Model Innovation in Retailing

Traditional retail practices are under stress as retailers ponder various ways of setting up a sustainable omnichannel business model. A significant challenge in their endeavor relates to the blurring lines between physical and digital worlds. This article analyzes three retailers’ exploratory efforts of alternative physical retail spaces. There are five key innovation areas to revamp for such a retail store: in-store technology, the role of sales associates, leveraging a mobile channel, data analytics, and collaborations. Moreover, physical retail space can serve as an aggregation hub that connects various retailer-customer interaction points across physical and digital spaces.
Molecular design aided by random forests and synthesis of potent trypanocidal agents as cruzain inhibitors for Chagas disease treatment

Cruzain is an established target for the identification of novel trypanocidal agents, but how good are in vitro/in vivo correlations? This work describes the development of a random forests model for the prediction of the bioavailability of cruzain inhibitors that are Trypanosoma cruzi killers. Some common properties that characterize drug‐likeness are poorly represented in many established cruzain inhibitors. This correlates with the evidence that many high‐affinity cruzain inhibitors are not trypanocidal agents against T. cruzi. On the other hand, T. cruzi killers that present typical drug‐like characteristics are likely to show better trypanocidal action than those without such features. The random forests model was not outperformed by other machine learning methods (such as artificial neural networks and support vector machines), and it was validated with the synthesis of two new trypanocidal agents. Specifically, we report a new lead compound, Neq0565, which was tested on T. cruzi Tulahuen (β‐galactosidase) with a pEC50 of 4.9. It is inactive in the host cell line showing a selectivity index (SI = EC50cyto/EC50T. cruzi) higher than 50.
CardioPy: An open-source heart rate variability toolkit for single-lead EKG

Background and Objective Heart rate variability (HRV) is a promising clinical marker of health and disease. Although HRV methodology is relatively straightforward, accurate detection of R-peaks remains a significant methodological challenge; this is especially true for single-lead EKG signals, which are routinely collected alongside EEG monitoring and for which few software options exist. Most developed algorithms with favorable R-peak detection profiles require significant mathematical and computational proficiency for implementation, providing a significant barrier for clinical research. Our objective was to address these challenges by developing a simple, free, and open-source software package for HRV analysis of single-lead EKG signals. Methods CardioPy was developed in python and optimized for short-term (5-minute) single-lead EKG recordings. CardioPy’s R-peak detection trades full automation and algorithmic complexity for an adaptive thresholding mechanism, manual artifact removal and parameter adjustment. Standard time and frequency domain analyses are included, such that CardioPy may be used as a stand-alone HRV analysis package. An example use-case of HRV across wakefulness and sleep is presented and results validated against the widely used Kubios HRV software. Results HRV analyses were conducted in 66 EKG segments collected from five healthy individuals. Parameter optimization was conducted or each segment, requiring ~1-3 minutes of manual inspection time. With optimization, CardioPy’s R-peak detection algorithm achieved a mean sensitivity of 100.0% (SD 0.05%) and positive predictive value of 99.8% (SD 0.20%). HRV results closely matched those produced by Kubios HRV, both by eye and by quantitative comparison; CardioPy power spectra explained an average of 99.7% (SD 0.50%) of the variance present in Kubios spectra. HRV analyses showed significant group differences between brain states; SDNN, low frequency power, and low frequency-to-high frequency ratio were reduced in slow wave sleep compared to wakefulness. Conclusions CardioPy provides an accessible and transparent tool for HRV analyses. Manual parameter optimization and artifact removal allow granular control over data quality and a highly reproducible analytic pipeline, despite additional time requirements. Future versions are slated to include automatic parameter optimization and a graphical user interface, further reducing analysis time and improving accessibility.
Co-Expression Networks in the Green Alga Chlamydomonas reinhardtii Empower Gene Discovery and Functional Exploration

The unicellular green alga Chlamydomonas reinhardtii is a choice reference system for the study of photosynthesis, cilium assembly and function, lipid and starch metabolism and metal homeostasis. Despite decades of research, the functions of thousands of genes remain largely unknown, and new approaches are needed to categorically assign genes to cellular pathways. Growing collections of transcriptome and proteome data now allow a systematic approach based on integrative co-expression analysis. We used a dataset comprising 518 deep transcriptome samples derived from 58 independent experiments to identify potential co-expression relationships between genes. We visualized co-expression potential with the R package corrplot, to easily assess co-expression and anti-correlation between genes from manually-curated and community-generated gene lists. We extracted 400 high-confidence cilia-related genes at the intersection of multiple co-expressed lists, illustrating the power of our simple method. Surprisingly, Chlamydomonas experiments did not cluster according to an obvious pattern, suggesting an underappreciated variable during sample collection. One possible source of variation may stem from the strong clustering of nuclear genes as a function of their diurnal phase, even in samples collected in constant conditions, indicating substantial residual synchronization in batch cultures. We provide a step-by-step guide into the analysis of co-expression across Chlamydomonas transcriptome datasets to help foster gene function discovery. One-sentence summary we reveal co-expression potential between Chlamydomonas genes and describe strong synchronization of cells grown in batch cultures as a possible source of underappreciated variation.
Exploring the factors causing the poor performance of most irrigation schemes in post-independence sub-Saharan Africa

ABSTRACT This article explores the factors causing the current poor performance of most government irrigation schemes in sub-Saharan Africa. The literature review finds that the poor performance is not primarily caused by socioeconomic and biophysical conditions inherent to sub-Saharan Africa. African farmers have adapted to diverse biophysical conditions and expanded or contracted their area under agricultural water management in response to market signals. Rather, this poor performance is predominantly linked to the production systems introduced during colonialism and developments since independence, such as agricultural policies restraining rural economic development, unsuitable irrigation technologies and agricultural practices, and international lending practices and trade arrangements.