The hand of Homo naledi

A nearly complete right hand of an adult hominin was recovered from the Rising Star cave system, South Africa. Based on associated hominin material, the bones of this hand are attributed to Homo naledi. This hand reveals a long, robust thumb and derived wrist morphology that is shared with Neandertals and modern humans, and considered adaptive for intensified manual manipulation. However, the finger bones are longer and more curved than in most australopiths, indicating frequent use of the hand during life for strong grasping during locomotor climbing and suspension. These markedly curved digits in combination with an otherwise human-like wrist and palm indicate a significant degree of climbing, despite the derived nature of many aspects of the hand and other regions of the postcranial skeleton in H. naledi

A case of rudimentory horn ectopic pregnancy

Ectopic pregnancy is emergency in obstetrics. Sometimes difficult to diagnose make it difficult to manage. There are various types of ectopic pregnancy and each possible a variety of challenges. This is a case of a 20-year-old who presented to R. L. Jalappa hospital, Kolar with history of 3 months of amenorrhea and complaints of pain abdomen. She was in state of shock and after evaluation taken up for emergency exploratory laparotomy where the diagnosis of ruptured horn ectopic of a uni-cornuate uterus was made and treated accordingly.

A multi-biometric iris recognition system based on a deep learning approach

YesMultimodal biometric systems have been widely applied in many real-world applications due to its ability to deal with a number of significant limitations of unimodal biometric systems, including sensitivity to noise, population coverage, intra-class variability, non-universality, and vulnerability to spoofing. In this paper, an efficient and real-time multimodal biometric system is proposed based on building deep learning representations for images of both the right and left irises of a person, and fusing the results obtained using a ranking-level fusion method. The trained deep learning system proposed is called IrisConvNet whose architecture is based on a combination of Convolutional Neural Network (CNN) and Softmax classifier to extract discriminative features from the input image without any domain knowledge where the input image represents the localized iris region and then classify it into one of N classes. In this work, a discriminative CNN training scheme based on a combination of back-propagation algorithm and mini-batch AdaGrad optimization method is proposed for weights updating and learning rate adaptation, respectively. In addition, other training strategies (e.g., dropout method, data augmentation) are also proposed in order to evaluate different CNN architectures. The performance of the proposed system is tested on three public datasets collected under different conditions: SDUMLA-HMT, CASIA-Iris- V3 Interval and IITD iris databases. The results obtained from the proposed system outperform other state-of-the-art of approaches (e.g., Wavelet transform, Scattering transform, Local Binary Pattern and PCA) by achieving a Rank-1 identification rate of 100% on all the employed databases and a recognition time less than one second per person

Novel Application of Single-Well Tracer Tests to Evaluate Hydraulic Stimulation Effectiveness

This paper presents a graphical method by which one can identify the number of fractures and their permeability distribution in the near-well region from single-well tracer tests. The method is an extension of tracer analysis methods developed previously to estimate flow geometry and relies on caluclating the relative fluid velocity from F-__ plots. A number of numerical examples show that high flow zones (fractures) are readily identified from the derivatives of an F-___ curve. The method can be used in evaluating well stimulation efforts by conducting a tracer test before and after the stimulation and comparing the velocity distributions

Structural hierarchies define toughness and defect-tolerance despite simple and mechanically inferior brittle building blocks

Mineralized biological materials such as bone, sea sponges or diatoms provide load-bearing and armor functions and universally feature structural hierarchies from nano to macro. Here we report a systematic investigation of the effect of hierarchical structures on toughness and defect-tolerance based on a single and mechanically inferior brittle base material, silica, using a bottom-up approach rooted in atomistic modeling. Our analysis reveals drastic changes in the material crack-propagation resistance (R-curve) solely due to the introduction of hierarchical structures that also result in a vastly increased toughness and defect-tolerance, enabling stable crack propagation over an extensive range of crack sizes. Over a range of up to four hierarchy levels, we find an exponential increase in the defect-tolerance approaching hundred micrometers without introducing additional mechanisms or materials. This presents a significant departure from the defect-tolerance of the base material, silica, which is brittle and highly sensitive even to extremely small nanometer-scale defects

Adaptability of the Novice School Heads on the Dimensions of Leadership Practices in SDO City of Malolos: Basis for Technical Assistance

This research study employed the mixed-method approach. Quantitative data were tabulated and treated using the SPSS. Meanwhile, the qualitative data were subjected to Thematic Analysis. Results revealed that on the general dimensions of leadership practices, the novice school heads showed total adaptability. However, after dissecting the answers of the participants, it showed that under each sub-dimension of the leadership practices, most of the novice school heads found research and innovation very challenging that they could not really adopt at present. Another sub-dimension includes updating of school files, policy reviews, managing resources and leading strategically. As to the experiences, some novice school heads gained understanding, became confident, and acknowledged the huge responsibilities of school leaders. Others also experienced the opposite such as the struggle to craft the School Improvement Plan, BED 1, 2, 3, Annual Improvement Plan, and liquidation of funds. It has been recommended by the researchers to conduct a division-wide leadership capacity training and provide re-calibration of technical assistance to the novice school heads so that they could adopt and function normally as responsible school leaders

Mathematical model for predicting solidification and cooling of steel inside mould and in air

A two-dimensional mathematical model has been developed to describe the solidification and cooling of steel inside the mould after teeming and in the air after stripping. Partial differential equations describing the processes have been discretized using control volume approach. The discretization equations obtained are of Tri-diagonal matrix form, which have been solved using well known Tri-diagonal matrix algorithm (TDMA) and Alternate direction implicit (ADI) solver. The model has been validated by measuring surface temperatures of mould and ingot using Infrared thermo-vision scanner. This is then used to compute charging temperature and solidification status of ingot as function of track time and type of ingot