Miracle-dz/UniFAR-FTUs huggingface dataset:
An Experimental Investigation of Document Vector Computation Methods for Sentiment Analysis of Turkish and English Reviews

Sentiment analysis is the task of identifying overall attitude of the given text documents by using text analysis and natural language processing techniques. In this study, we present experimental results of sentiment analysis on movie and product reviews datasets that are in Turkish and English languages by using a Support Vector Machine (SVM) classifier. Moreover, we compare different document vector computation techniques and show their effects on the sentiment analysis. We empirically evaluate SVM types, kernel types, weighting schemes such as TF or TF*IDF, TF variances, IDF variances, tokenization methods, feature selection systems, text preprocessing techniques and vector normalizations. We have obtained 91.33% accuracy as the best on our collected Turkish product reviews dataset by using C-SVC SVM type with linear kernel, log normalization TF* probabilistic IDF weighting scheme, L2 vector normalization, Chi-square feature selection, and unigram word tokenization. A very detailed comparison of the document vector computation methods over Turkish and English datasets are also presented.
Genetic and genomic monitoring with minimally invasive sampling methods

The decreasing cost and increasing scope and power of emerging genomic technologies are reshaping the field of molecular ecology. However, many modern genomic approaches (e.g., RAD‐seq) require large amounts of high‐quality template DNA. This poses a problem for an active branch of conservation biology: genetic monitoring using minimally invasive sampling (MIS) methods. Without handling or even observing an animal, MIS methods (e.g., collection of hair, skin, faeces) can provide genetic information on individuals or populations. Such samples typically yield low‐quality and/or quantities of DNA, restricting the type of molecular methods that can be used. Despite this limitation, genetic monitoring using MIS is an effective tool for estimating population demographic parameters and monitoring genetic diversity in natural populations. Genetic monitoring is likely to become more important in the future as many natural populations are undergoing anthropogenically driven declines, which are unlikely to abate without intensive adaptive management efforts that often include MIS approaches. Here, we profile the expanding suite of genomic methods and platforms compatible with producing genotypes from MIS, considering factors such as development costs and error rates. We evaluate how powerful new approaches will enhance our ability to investigate questions typically answered using genetic monitoring, such as estimating abundance, genetic structure and relatedness. As the field is in a period of unusually rapid transition, we also highlight the importance of legacy data sets and recommend how to address the challenges of moving between traditional and next‐generation genetic monitoring platforms. Finally, we consider how genetic monitoring could move beyond genotypes in the future. For example, assessing microbiomes or epigenetic markers could provide a greater understanding of the relationship between individuals and their environment.
Exercise Reduces Dopamine D1R and Increases D2R in Rats: Implications for Addiction

Introduction Exercise has been shown to be effective for preventing and treating substance abuse in both clinical and preclinical studies. Less is known, however, regarding the underlying neurobiological mechanisms driving these changes in drug-seeking behavior. One possibility is that exercise may alter the mesolimbic dopamine pathway in such a way that makes drugs of abuse less salient and/or rewarding. Methods To examine possible exercise-induced changes in dopamine signaling, male and female Lewis rats were split into exercise and sedentary groups at 8 wk of age. Exercise rats were run on a treadmill at 10 m·min−1, 5 d·wk−1, for 6 wk, whereas sedentary rats remained in their home cage. Rats were killed after the 6 wk of treatment, and their brains were used for in vitro autoradiography using [3H]SCH 23,390, [3H]Spiperone, and [3H]WIN55,428 ligands to quantify dopamine type 1-like receptor (D1R)-like, dopamine type 2-like receptor (D2R)-like, and dopamine transporter binding, respectively. Results Exercised rats had 18% and 21% lower D1R-like binding levels compared to sedentary rats within the olfactory tubercle and nucleus accumbens shell, respectively. In addition, male and female exercise rats showed greater D2R-like binding levels within the dorsomedial caudate putamen (30%), ventrolateral caudate putamen (24%), and ventromedial caudate putamen (27%), as well as the olfactory tubercle (19%). Greater D2R-like binding in the nucleus accumbens core (24%) and shell (25%) of exercised rats compared with sedentary rats approached significance. No effects were found for dopamine transporter binding. Conclusions These findings support the hypothesis that aerobic exercise results in changes in the mesolimbic pathway that could mediate exercise-induced attenuation of drug-seeking behavior.
Novel Signal Noise Reduction Method through Cluster Analysis, Applied to Photoplethysmography

Physiological signals can often become contaminated by noise from a variety of origins. In this paper, an algorithm is described for the reduction of sporadic noise from a continuous periodic signal. The design can be used where a sample of a periodic signal is required, for example, when an average pulse is needed for pulse wave analysis and characterization. The algorithm is based on cluster analysis for selecting similar repetitions or pulses from a periodic single. This method selects individual pulses without noise, returns a clean pulse signal, and terminates when a sufficiently clean and representative signal is received. The algorithm is designed to be sufficiently compact to be implemented on a microcontroller embedded within a medical device. It has been validated through the removal of noise from an exemplar photoplethysmography (PPG) signal, showing increasing benefit as the noise contamination of the signal increases. The algorithm design is generalised to be applicable for a wide range of physiological (physical) signals.
Tumor-Specific CD4+ T Lymphocytes from Cancer Patients Are Required for Optimal Induction of Cytotoxic T Cells Against the Autologous Tumor

This study focuses on the specific CD4+ T cell requirement for optimal induction of cytotoxicity against MHC class II negative autologous tumors (AuTu) collected from patients with various types of cancer at advanced stages. CD4+ T cells were induced in cultures of cancer patients’ malignant effusion-associated mononuclear cells with irradiated AuTu (mixed lymphocyte tumor cultures (MLTC)) in the presence of recombinant IL-2 and recombinant IL-7. Tumor-specific CD4+ T cells did not directly recognize the AuTu cells, but there was an MHC class II-restricted cross-priming by autologous dendritic cells (DCs), used as APC. CD8+ CTL, also induced during the MLTC, lysed specifically AuTu cells or DCs pulsed with AuTu peptide extracts (acid wash extracts (AWE)) in an MHC class I-restricted manner. Removal of CD4+ T cells or DCs from the MLTC drastically reduced the CD8+ CTL-mediated cytotoxic response against the AuTu. AWE-pulsed DCs preincubated with autologous CD4+ T cells were able, in the absence of CD4+ T cells, to stimulate CD8+ T cells to lyse autologous tumor targets. Such activated CD8+ T cells produced IL-2, IFN-γ, TNF-α, and GM-CSF. The process of the activation of AWE-pulsed DCs by CD4+ T cells could be inhibited with anti-CD40 ligand mAb. Moreover, the role of CD4+ T cells in activating AWE-pulsed DCs was undertaken by anti-CD40 mAb. Our data demonstrate for the first time in patients with metastatic cancer the essential role of CD4+ Th cell-activated DCs for optimal CD8+ T cell-mediated killing of autologous tumors and provide the basis for the design of novel protocols in cellular adoptive immunotherapy of cancer, utilizing synthetic peptides capable of inducing T cell help in vivo.
Two-dimensional numerical investigations on the termination of bilinear flow in fractures

Abstract. Bilinear flow occurs when fluid is drained from a permeable matrix by producing it through an enclosed fracture of finite conductivity intersecting a well along its axis. The terminology reflects the combination of two approximately linear flow regimes: one in the matrix with flow essentially perpendicular to the fracture, and one along the fracture itself associated with the non-negligible pressure drop in it. We investigated the characteristics, in particular the termination, of bilinear flow by numerical modeling allowing for an examination of the entire flow field without prescribing the flow geometry in the matrix. Fracture storage capacity was neglected relying on previous findings that bilinear flow is associated with a quasi-steady flow in the fracture. Numerical results were generalized by dimensionless presentation. Definition of a dimensionless time that, other than in previous approaches, does not use geometrical parameters of the fracture permitted identifying the dimensionless well pressure for the infinitely long fracture as the master curve for type curves of all fractures with finite length from the beginning of bilinear flow up to fully developed radial flow. In log–log scale the master curve's logarithmic derivative initially follows a 1/4-slope straight line (characteristic for bilinear flow) and gradually bends into a horizontal line (characteristic for radial flow) for long times. During the bilinear flow period, isobars normalized to well pressure propagate with the fourth and second root of time in fracture and matrix, respectively. The width-to-length ratio of the pressure field increases proportional to the fourth root of time during the bilinear period, and starts to deviate from this relation close to the deviation of well pressure and its derivative from their fourth-root-of-time relations. At this time, isobars are already significantly inclined with respect to the fracture. The type curves of finite fractures all deviate counterclockwise from the master curve instead of clockwise or counterclockwise from the 1/4-slope straight line as previously proposed. The counterclockwise deviation from the master curve was identified as the arrival of a normalized isobar reflected at the fracture tip 16 times earlier. Nevertheless, two distinct regimes were found in regard to pressure at the fracture tip when bilinear flow ends. For dimensionless fracture conductivities TD 10, the pressure at the fracture tip has reached substantial fractions of the associated change in well pressure when the flow field transforms towards intermittent formation linear flow at times that scale inversely with the fourth power of dimensionless fracture conductivity. Our results suggest that semi-log plots of normalized well pressure provide a means for the determination of hydraulic parameters of fracture and matrix after shorter test duration than for conventional analysis.
Influence of Inherent Surface and Internal Defects on Mechanical Properties of Additively Manufactured Ti6Al4V Alloy: Comparison between Selective Laser Melting and Electron Beam Melting

Additive manufacture (AM) appears to be the most suitable technology to produce sophisticated, high quality, lightweight parts from Ti6Al4V alloy. However, the fatigue life of AM parts is of concern. In our study, we focused on a comparison of two techniques of additive manufacture—selective laser melting (SLM) and electron beam melting (EBM)—in terms of the mechanical properties during both static and dynamic loading. All of the samples were untreated to focus on the influence of surface condition inherent to SLM and EBM. The EBM samples were studied in the as-built state, while SLM was followed by heat treatment. The resulting similarity of microstructures led to comparable mechanical properties in tension, but, due to differences in surface roughness and specific internal defects, the fatigue strength of the EBM samples reached only half the value of the SLM samples. Higher surface roughness that is inherent to EBM contributed to multiple initiations of fatigue cracks, while only one crack initiated on the SLM surface. Also, facets that were formed by an intergranular cleavage fracture were observed in the EBM samples.
Simulation Study of Autonomous Drive for Active Capsule Endoscopy

Recently, external electromagnetic actuation(EMA) system was introduced to control the locomotion of the capsule endoscopy(CE) using magnetic force. EMA system provides the manual user interface to control the system, but inspectors suffered from fatigues due to the long examination time. We proposed an autonomous driving algorithm for the capsule endoscope. The algorithm searched the target point based on the image processing where the capsule should orient, and the steering was automatically manipulated until the capsule oriented the target point. Then, the propulsion was made until the capsule deviated from the target point. In order to verify the feasibility of the algorithm, simulated endoscopic images were acquired from the commercially available endoscopic capsule by using intestine phantom and a linear and rotation motion stage. The driving simulator was tested on the arc-shaped paths having the various curvatures under the various propulsion forces. In the most conditions, the proposed algorithm succeeded in driving autonomously in the given paths. In some conditions, having a large curvature and a large propulsion, the target point was missed, but scanning algorithm for the missed target point may overcome this problem. In conclusion, the proposed algorithm could be utilized in the active capsule endoscope system and provide the autonomous driving mode in the capsule endoscopy without additional sensors or devices.
Basic Level Categorization Facilitates Visual Object Recognition

Recent advances in deep learning have led to significant progress in the computer vision field, especially for visual object recognition tasks. The features useful for object classification are learned by feed-forward deep convolutional neural networks (CNNs) automatically, and they are shown to be able to predict and decode neural representations in the ventral visual pathway of humans and monkeys. However, despite the huge amount of work on optimizing CNNs, there has not been much research focused on linking CNNs with guiding principles from the human visual cortex. In this work, we propose a network optimization strategy inspired by both of the developmental trajectory of children's visual object recognition capabilities, and Bar (2003), who hypothesized that basic level information is carried in the fast magnocellular pathway through the prefrontal cortex (PFC) and then projected back to inferior temporal cortex (IT), where subordinate level categorization is achieved. We instantiate this idea by training a deep CNN to perform basic level object categorization first, and then train it on subordinate level categorization. We apply this idea to training AlexNet (Krizhevsky et al., 2012) on the ILSVRC 2012 dataset and show that the top-5 accuracy increases from 80.13% to 82.14%, demonstrating the effectiveness of the method. We also show that subsequent transfer learning on smaller datasets gives superior results.
A Systematic Study of RNAi Effects and dsRNA Stability in Tribolium castaneum and Acyrthosiphon pisum, Following Injection and Ingestion of Analogous dsRNAs

RNA interference (RNAi) effects in insects are highly variable and may be largely dependent upon the stability of introduced double-stranded RNAs to digestion by nucleases. Here, we report a systematic comparison of RNAi effects in susceptible red flour beetle (Tribolium castaneum) and recalcitrant pea aphid (Acyrthosiphon pisum) following delivery of dsRNAs of identical length targeting expression of V-type ATPase subunit E (VTE) and inhibitor of apoptosis (IAP) genes. Injection and ingestion of VTE and IAP dsRNAs resulted in up to 100% mortality of T. castaneum larvae and sustained suppression (>80%) of transcript levels. In A. pisum, injection of VTE but not IAP dsRNA resulted in up to 65% mortality and transient suppression (ca. 40%) of VTE transcript levels. Feeding aphids on VTE dsRNA reduced growth and fecundity although no evidence for gene suppression was obtained. Rapid degradation of dsRNAs by aphid salivary, haemolymph and gut nucleases contrasted with stability in T. castaneum larvae where it appears that exo-nuclease activity is responsible for relatively slow digestion of dsRNAs. This is the first study to directly compare RNAi effects and dsRNA stability in receptive and refractory insect species and provides further evidence that dsRNA susceptibility to nucleases is a key factor in determining RNAi efficiency.
Evaluation and application of the CPM Dairy Nutrition model

SUMMARY The Cornell-Penn-Miner (CPM) Dairy is an applied mathematical nutrition model that computes dairy cattle requirements and the supply of energy and nutrients based on characteristics of the animal, the environment and the physicochemical composition of the feeds under diverse production scenarios. The CPM Dairy was designed as a steady-state model to use rates of degradation of feed carbohydrate and protein and the rate of passage to estimate the extent of ruminal fermentation, microbial growth, and intestinal digestibility of carbohydrate and protein fractions in computing energy and protein post-rumen absorption, and the supply of metabolizable energy and protein to the animal. The CPM Dairy version 3.0 (CPM Dairy 3.0) includes an expanded carbohydrate fractionation scheme to facilitate the characterization of individual feeds and a sub-model to predict ruminal metabolism and intestinal absorption of long chain fatty acids. The CPM Dairy includes a non-linear optimization algorithm that allows for least-cost formulation of diets while meeting animal performance, feed availability and environmental restrictions of modern dairy cattle production. When the CPM Dairy 3.0 was evaluated with data of 228 individual lactating dairy cows containing appropriate information including observed dry matter intake, the linear regression between observed and model-predicted milk production values indicated the model was able to account for 79·8% of the variation. The concordance correlation coefficient (CCC) was high (rc=0·89) without a significant mean bias (0·52 kg/d; P=0·12). The accuracy estimated by the CCC was 0·997. The root of mean square error of prediction (MSEP) was 5·14 kg/d (0·16 of the observed mean) and 87·3% of the MSEP was due to random errors, suggesting little systematic bias in predicting milk production of high-producing dairy cattle. Based upon these evaluations, it was concluded the CPM Dairy 3.0 model adequately predicts milk production at the farm level when appropriate animal characterization, feed composition and feed intake are provided; however, further improvements are needed to account for individual animal variation.
Differential Distribution of Salmonella Serovars and Campylobacter spp. Isolates in Free-Living Crows and Broiler Chickens in Aomori, Japan

Salmonella and Campylobacter cause foodborne enteritis mainly via the consumption of raw/undercooked contaminated poultry meat and products. Broiler flocks are primarily colonized with these bacteria; however, the underlying etiology remains unclear. The present study was conducted in order to obtain further information on the prevalence and genotypic distribution of Salmonella and Campylobacter in free-living crows and broiler flocks in a region for 2 years, thereby facilitating estimations of the potential risk of transmission of C. jejuni from crows to broiler flocks. Salmonella serovars Bredeney and Derby were isolated from 8 and 3 out of 123 captured crows, respectively, both of which are not common in broiler chickens. Campylobacter were isolated from all 89 crows tested and C. jejuni was prevalent (85 crows). Pulsed field gel electrophoresis showed broad diversity in the crow isolates of C. jejuni. However, 3 crow isolates and 2 broiler isolates showing similar banding patterns were assigned to different sequence types in multi-locus sequence typing. These results indicate that crows do not share Salmonella serovars with broilers, and harbor various genotypes of C. jejuni that differ from those of broiler flocks. Thus, our results indicate that crows are not a potential vector of these bacteria to broiler flocks in this region.
Biodistribution and Dosimetry Results from a Phase 1 Trial of Therapy with the Antibody–Radionuclide Conjugate 177Lu-Lilotomab Satetraxetan

177Lu-lilotomab satetraxetan is a novel antibody–radionuclide conjugate currently in a phase 1/2a first-in-humans dose escalation trial for patients with relapsed CD37-positive indolent non-Hodgkin lymphoma. The aim of this study was to investigate biodistribution and absorbed doses to organs at risk. Methods: In total, 7 patients treated with 177Lu-lilotomab satetraxetan were included for dosimetry. Patients were grouped on the basis of 2 different predosing regimens (with and without predosing with 40 mg of lilotomab) and were treated with different levels of activity per body weight (10, 15, and 20 MBq/kg). All patients were pretreated with rituximab. Serial planar and SPECT/CT images were used to determine time–activity curves and patient-specific masses for organs with 177Lu-lilotomab satetraxetan uptake. Doses were calculated with OLINDA/EXM. Results: The organs (other than red bone marrow and tumors) with distinct uptake of 177Lu-lilotomab satetraxetan were the liver, spleen, and kidneys. The highest uptake was found in the spleen, with doses ranging from 1.54 to 3.60 mGy/MBq. The liver received 0.70–1.15 mGy/MBq. The kidneys received the lowest dose of the source organs investigated, 0.16–0.79 mGy/MBq. No statistically significant differences in soft-tissue absorbed doses were found between the two predosing regimens. The whole-body dose ranged from 0.08 to 0.17 mGy/MBq. Conclusion: The biodistribution study for patients treated with 177Lu-lilotomab satetraxetan revealed the highest physiologic uptake to be in the liver and spleen (besides the red marrow). For all treatment levels investigated, the absorbed doses were found to be modest when compared with commonly assumed tolerance limits.
Scalp-Implantable Antenna Systems for Intracranial Pressure Monitoring

This communication proposes miniaturized implantable antenna systems for biomedical applications, specifically for scalp implantation. The proposed designs exhibit dual-band characteristics on the industrial, scientific, and medical bands (i.e., 915 and 2450 MHz) with small volumes: 344 mm<sup>3</sup> (System A) and 406 mm<sup>3</sup> (System B). Each system is integrated with the microelectronic components and a battery. The key feature of the proposed implantable antenna is its small volume (<inline-formula> <tex-math notation="LaTeX">$8 \times 6 \times 0.5$ </tex-math></inline-formula> = 24 mm<sup>3</sup>) with a slotless and a vialess ground plane, thereby reducing design complexity. Moreover, the structure exhibits satisfactory peak gain values of −28.5 and −22.8 dBi at a lower and higher resonant band, respectively. Simulations using the finite-element method and finite-difference time domain are performed to evaluate the implantable systems. For validation, measurements are carried out in a saline solution. The antenna offers a good agreement between the measured and simulation results. In addition, a link budget is calculated to analyze the data transmission range.