Seeing the Forest for the trees: Assessing genetic offset predictions with Gradient Forest

Gradient Forest (GF) is increasingly being used to forecast climate change impacts, but remains mostly untested for this purpose. We explore its robustness to assumption violations, and relationship to measures of fitness, using SLiM simulations with explicit genome architecture and a spatial metapopulation. We evaluate measures of GF offset in: (1) a neutral model with no environmental adaptation; (2) a monogenic "population genetic" model with a single environmentally adapted locus; and (3) a polygenic "quantitative genetic" model with two adaptive traits, each adapting to a different environment. Although we found GF Offset to be broadly correlated with fitness offsets under both single locus and polygenic architectures. It could also be confounded by neutral demography, genomic architecture, and the nature of the adaptive environment. GF Offset is a promising tool, but it is important to understand its limitations and underlying assumptions, especially when used in the context of forecasting maladaptation.

Providing Treatment in a Prison-Based Therapeutic Community for Those Who Have Committed Sexual Offences

This article explores some of the difficulties inherent in managing risk in those who have committed sexual or other violent offences and how this may impact on their ability to re-integrate into the community. It discusses the work undertaken at HMP Grendon, a prison-based therapeutic community (TC), to address these difficulties and help residents develop a pro-social lifestyle starting in custody and continuing on release. The article aims to describe how the TC model offers a containing and adaptive environment, and how this can provide opportunities to address offence-related behaviour, which is not always possible in other prison settings. Furthermore, it describes some of the difficulties inherent in undertaking work of this nature, in the need for an accurate understanding of the relevant areas of risk, and the tensions developing a therapeutic relationship with individuals with complex needs. Methods of assessment of risk and need are discussed, and how they are used in a collaborative manner to have the most accurate picture of what will help residents to maintain their pro-social lifestyle on release.

Implementasi SUpport Vector Machine untuk Deteksi Stres pada Pengguna E-Learning

<p>Pada masa ini, e-learning cenderung monoton yang hanya digunakan untuk otomasi pekerjaan saja. Pada pengembangan e-learning yang akan datang, e-learning menerapkan lingkungan adaptif agar hasil yang didapatkan dari penggunaan e-learning dapat menjadi lebih optimal. Salah satu strategi agar e-learning menjadi adaptif adalah adaptasi dengan kondisi mental pengguna. Contoh kasus ketika pengguna stres maka sistem e-learning yang adaptif akan memberikan materi latihan yang lebih mudah atau memberi notifikasi untuk istirahat. Deteksi stres dapat dilakukan dengan pengolahan data dari sinyal fisiologis, yaitu <em>heart rate. </em>Metode klasifikasi <em>Support Vector Machine</em> diterapkan untuk deteksi stres. Fitur yang digunakan untuk klasifikasi stres adalah fitur yang berasal dari domain <em>Heart Rate Statistical</em>. Pengujian akurasi metode <em>Support Vector Machine </em>terhadap kasus pengguna e-learning mampu menghasilkan akurasi sampai 58,3% dengan menggunakan 12 sampel data.</p><p> </p><p><em><strong>Abstract</strong></em></p><p class="Abstract"><em>This time, e-learning tends to be monotonous which is only for job automation. In future of e-learning development, e-learning will apply adaptive environment so that the result obtained from e-learning can be more optimal. One of the strategies to turn e-learning to be adaptive is adaptation to user’s mental condition. By example, when user is stressed then adaptive e-learning system will provide easier exercise or pop notification for break. Stress detection can be achieved by processing data from physiological signal that is heart rate. The Support Vector Machine classification method can be implemented for stress detection. The features that used for stress detection are derived features from Heart Rate Statistical domain. The Support Vector Machine validation testing on case of e-learning users able to provide 58,3% accuracy by using 12 samples of data.<strong></strong></em></p><p><em><strong><br /></strong></em></p>

Length-weight Relationship of Heterobranchus bidorsalis (Geoffroy st. Hilaire 1809) Diploid and Triploid Progenies raised under the same Environmental condition

Twenty specimens of triploid with weight and length ranging from 207-300g and 29-32cm; diploid 150-200g and 23-28cm Heterobranchus bidorsalis (Geoffroy St. Hilaire 1809) were subjected to morphometric and meristic characterization, length-weight relationship and condition factor evaluation. Triploid specimens had the higher values in all the parameters examined and were significantly different (P<0.005). Regression analysis of diploid and triploid show the ranges of values (K) of 0.802 1.453 and 0.838 0.906 respectively, for condition factor (k) while the relative condition factor values (Kn) ranged between 0.869 1.087 and 0.968 1.038 respectively. Weight increases directly as the total length increases for both diploid and triploid indicating isometric growth. The R2 in triploid was higher (96.8%) than in diploids (42.4%). In diploid progenies, the length by weight was significantly different (P<0.05) in triploid. Triploid progenies need no special adaptive environment or technique for rearing. Therefore, diploid and triploid progenies can be successfully cultured simultaneously under the same environmental condition.

Strategy of Interaction of the State and Small Business as a Factor of Innovative Development in the Republic Kazakhstan

The present article examines the strategy of interaction of the state and small business as a factor of innovative development – which is a very topical issue, since small innovative businesses are enterprises that are on the balance of industrial property applied objects (patents, utility models, industrial designs), as well as those that systematize and protect intellectual property from commercial secrets. At the same time, the innovation activity of small business, according to the authors, is not a custom-made industry, as a rule, this industry requires more development than funding. In this connection, for the formation of innovative forms and the implementation of their activities, commercialization, expansion of strategic management, and the accession of subjects of state innovation institutions, it is necessary to create an adaptive environment for the development of small business.