Original Trace Research Articles

Peculiarities of conducting an examination during the investigation of sexual criminal offenses

It has been emphasized that during the formation of the methodology of the investigation of sexual criminal offenses, it is necessary to highlight the procedural and tactical features of conducting individual investigative (search) actions. The necessity of distinguishing and characterizing the peculiarities of conducting an examination during the investigation of sexual criminal offenses has been substantiated. The importance of examination during the investigation of sexual criminal offenses has been revealed. It has been noted that the procedural procedure for conducting an examination during a pre-trial investigation of the investigated category of criminal offenses is defined in Part 3 of Art. 214, Art. Art. 223, 233, 237-239, 615 of the Criminal Procedure Code of Ukraine. It has been found that the main tasks of the review during the investigation of sexual criminal offenses are: the search for traces of biological origin that could have been left by the offender and may later become objects of his identification, the detection of technical means of recording sexual acts and their broadcast, the detection of pornographic products , draft records, etc. Forensic recommendations on the tactics of conducting an examination have been formed, taking into account the type of criminal offense under investigation, the specifics of the trace picture, the type of examination and the stage of its conduct. It has been determined the peculiarities of the inspection of the area, which is the place of the event; the premises, which is the place of the event; things and documents (clothes and shoes of the victim and the suspect, notebooks, photos and videos, computers, mobile phones, etc.). The specifics of the review tactics of information and telecommunication systems, computer equipment and devices with a telephone function, which were used as means of preparation, direct commission and concealment of sexual criminal offenses, have been clarified..

Rapid identification of Radix Astragali origin by using fluorescence probe combined with chemometrics

Fluorescent probes for metal ion recognition can be divided into selective probes, weakly selective probes, and non-selective probes roughly. Weakly selective probes are not often used for quantitative analysis of metal ions due to their overlapping spectra resulting from simultaneous interactions with multiple metal ions. Conversely, the different metal ions contained in herbal medicine extracts from different geographical origins will produce corresponding fluorescence fingerprint profiles after interaction with weakly selective fluorescence probes. The performance can be used in the study of origin tracing of food or Chinese herbal medicine. Weakly selective fluorescent probes of benzimidazole derivatives have been synthesized and attempted to be used in the origin tracing of Radix Astragali in this work. Radix Astragali from different origins will produce different fluorescence fingerprint spectra due to the difference of metal ions and content in combination with the probe. Excitation-emission matrix (EEM) fluorescence spectroscopy in conjunction with N-way partial least squares discriminant analysis (N-PLS-DA), and unfolded partial least squares discriminant analysis (U-PLS-DA) were used to identify the origin of 150 Radix Astragali samples from five geographical origins. The prediction results showed that the correct recognition rates of the U-PLS-DA model and N-PLS-DA model are 95.92% and 93.88%, respectively. In comparison, the results of U-PLS-DA are slightly better than those of N-PLS-DA. These findings indicate that EEM fluorescence spectroscopy based on weakly selective fluorescent probes combined with multi-way chemometrics provides a good idea for the origin tracing of traditional Chinese medicine.

Distinct engrams control fear and extinction memory.

Memories are stored in engram cells, which are necessary and sufficient for memory recall. Recalling a memory might undergo reconsolidation or extinction. It has been suggested that the original memory engram is reactivated during reconsolidation so that memory can be updated. Conversely, during extinction training, a new memory is formed that suppresses the original engram. Nonetheless, it is unknown whether extinction creates a new engram or modifies the original fear engram. In this study, we utilized the Daun02 procedure, which uses c-Fos-lacZ rats to induce apoptosis of strongly activated neurons and examine whether a new memory trace emerges as a result of a short or long reactivation, or if these processes rely on modifications within the original engram located in the basolateral amygdala (BLA) and infralimbic (IL) cortex. By eliminating neurons activated during consolidation and reactivation, we observed significant impacts on fear memory, highlighting the importance of the BLA engram in these processes. Although we were unable to show any impact when removing the neurons activated after the test of a previously extinguished memory in the BLA, disrupting the IL extinction engram reactivated the aversive memory that was suppressed by the extinction memory. Thus, we demonstrated that the IL cortex plays a crucial role in the network involved in extinction, and disrupting this specific node alone is sufficient to impair extinction behavior. Additionally, our findings indicate that extinction memories rely on the formation of a new memory, supporting the theory that extinction memories rely on the formation of a new memory, whereas the reconsolidation process reactivates the same original memory trace.

Petrophysical Property Prediction from Seismic Inversion Attributes Using Rock Physics and Machine Learning: Volve Field, North Sea

An accurate petrophysical model of the subsurface is essential for resource development and CO2 sequestration. We present a new workflow that provides a high-resolution estimate of petrophysical reservoir properties using seismic data with rock physics modeling and machine-learning techniques (i.e., deep learning neural networks). First, we compare the sequential prediction of the following petrophysical attributes: mineralogy, porosity, and fluid saturation, with the simultaneous prediction of all of the properties using the Volve field in the Norwegian North Sea as an example. The workflow shows that the sequential prediction produces a more efficient and accurate classification of petrophysical properties (the RMS error between the predicted and the original seismic trace is 50% smaller for the sequential compared to the simultaneous procedure). Next, the seismic amplitude response of the reservoirs was studied using rock physics modeling and amplitude versus offset (AVO) analysis to distinguish the different lithologies and fluid types. To ascertain the optimal hydrocarbon production areas, we performed Bayesian seismic inversion and applied machine learning to estimate the petrophysical properties. We examined how porosity, Vclay, and fluid variations affect the elastic properties. In Poisson’s ratio versus the P-wave impedance domain, a 10% porosity increase decreases the acoustic impedance (AI) by 30%, while a 20% Vclay decrease increases the AI by 12%. The Utsira Formation in the Volve field (5 km north of the Sleipner Øst field) was evaluated as a potential CO2 geological storage unit using Gassmann fluid substitution and seismic modeling. We look to assess the elastic property variation caused by CO2 saturation changes for monitoring purposes and simulate the effect. In the first 10% CO2 substitution, the P-wave velocity decrease is 12%, a subtle effect is observed for higher CO2 saturation values, and S-wave velocity (Vs) increases with CO2 saturation. Our analysis aspires to assist future reservoir studies and CO2 sequestration in similar fields.

Abstract A006: Cancer origin tracing and timing in two high risk prostate cancers using multisample whole genome analysis: Potential clinical value

Abstract Prostate cancer (PrCa) genomic heterogeneity causes resistance to therapies such as androgen deprivation. Such heterogeneity can be deciphered in the context of evolutionary principles, but current clinical trials do not include evolution as an essential feature. Understanding the evolution of an individual PrCa through serial analysis in space and time may be more important than identifying actionable targets for therapy from single samples as in current practice. The most prominent recent example of this is our recent evolution-based discovery of subclone eradication in a metastatic PrCa, with subsequent identification of a novel method to compare eradicated and resistant subclones to better resolve actionable targets for therapy. Whether or not analysis of genomic data in an evolutionary context in primary prostate cancer can provide unique added value in the research and clinical domains remains an open question. We used novel processing techniques to obtain whole genome data together with 3D anatomic and histomorphologic analysis in two men (GP5 and GP12) with high risk PrCa undergoing radical prostatectomy. A total of 22 whole genome-sequenced sites (16 primary cancer foci and 6 lymph node metastatic) were analyzed using evolutionary reconstruction tools and spatio-evolutionary models. Probability models were used to trace spatial and chronological origins of the primary tumor and metastases, chart their genetic drivers, and distinguish metastatic and non-metastatic subclones. In patient GP5, CDK12 inactivation was among the first mutations, leading to a PrCa tandem duplicator phenotype and initiating the cancer around age 50, followed by rapid cancer evolution after age 57, and metastasis around age 59, five years prior to prostatectomy. In patient GP12, accelerated cancer progression was detected after age 54, and metastasis occurred around age 56, three years prior to prostatectomy. Multiple metastasis-originating events were identified in each patient and tracked anatomically. Metastasis from prostate to lymph nodes occurred strictly ipsilaterally in all 12 detected events. In this pilot, metastatic subclone content analysis appears to substantially enhance identification of key drivers. Evolutionary analysis’ potential impact on therapy selection appears positive in these pilot cases. Taken together with our recent discovery that solid tumor subclones can be eradicated, and that comparison of eradicated and resistant subclones could guide therapy, we believe the case for embarking on clinical trials testing evolutionary-analysis informed PrCa care is compelling. PrCa evolutionary analysis allows tracking of anatomic site of origin, timing of cancer origin and spread, and distinction of metastatic-capable from non-metastatic subclones. This enables better identification of actionable targets for therapy. If extended to larger cohorts, it appears likely that similar analyses could add substantial biological insight and clinically relevant value. Citation Format: Anssi Nurminen, Serafiina Jaatinen, Sinja Taavitsainen, Gunilla Högnäs, Tom Lesluyes, Naser Ansari-Pour, Teemu Tolonen, Kerstin Haase, Antti Koskenalho, Matti Kankainen, Juho Jasu, Hanna Rauhala, Jenni Kesäniemi, Tiia Nikupaavola, Paula Kujala, Irina Rinta-Kiikka, Jarno Riikonen, Antti Kaipia, Teemu Murtola, Teuvo L. Tammela, Tapio Visakorpi, Matti Nykter, David C. Wedge, Peter Van Loo, G. Steven Bova. Cancer origin tracing and timing in two high risk prostate cancers using multisample whole genome analysis: Potential clinical value [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr A006.

RETRACTED: DL-SCA: An deep learning based approach for intra-class CutMix data augmentation

CutMix data augmentation can provide a large amount of augmented data for DL-SCA (deep learning side channel attacks) by generating new power traces. However, traces generated by CutMix may lose dependency with the new label, which may reduce the accuracy of the training model. In light of this, we propose an improved intra-class CutMix data augmentation method. Firstly, the original power traces are classified by the label. Then, the original power traces are selected by the same label constraint to generate new power traces according to CutMix, which can ensure the dependency between the generated trace and its label. Furthermore, to maintain balance among different classified datasets, the traces are generated sequentially according to distinct labels. Finally, based on the augmented power traces, the MLP (Multilayer Perceptron) and CNN (Convolutional Neural Network) models can be constructed and trained to recover the key of AES. In order to verify the effectiveness of the proposed method, we conducted experimental evaluations using the MLP and CNN models based on DPA-contest v4 dataset and ASCAD dataset. The test results show that the generated traces based on the intra-class CutMix method can be very similar to the original power traces, and the MLP and CNN models can be effectively trained based on the generated traces to recover the key of AES. Compared with existing data augmentation methods, the proposed method can complete the key recovery with faster convergence and fewer power traces.

Engrams of Fear Memory Attenuation.

Fear attenuation is an etiologically relevant process for animal survival, since once acquired information needs to be continuously updated in the face of changing environmental contingencies. Thus, when situations are encountered that were originally perceived as fearful but are no longer so, fear must be attenuated, otherwise, it risks becoming maladaptive. But what happens to the original memory trace of fear during fear attenuation? In this chapter, we review the studies that have started to approach this question from an engram perspective. We find evidence pointing to both the original memory trace of fear being suppressed, as well as it being updated towards safety. These seemingly conflicting results reflect a well-established dichotomy in the field of fear memory attenuation, namely whether fear attenuation is mediated by an inhibitory mechanism that suppresses fear expression, called extinction, or by an updating mechanism that allows the fear memory to reconsolidate in a different form, called reconsolidation-updating. Which of these scenarios takes the upper hand is ultimately influenced by the behavioral paradigms used to induce fear attenuation, but is an important area for further study as the precise cell populations underlying fear attenuation and the molecular mechanisms therein can now be understood at unprecedented resolution.

Emergence of crucial evidence catalyzing the origin tracing of SARS-CoV-2.

Since the emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), its genetic and geographical origins remain unclear, resulting in suspicions about its natural origin. In one of our previous studies, we reported the presence of a furin cleavage site RRAR in the junction region between S1 and S2 subunits of the spike protein, which was discovered as the first crucial clue for the origin tracing of SARS-CoV-2. In the present study, we conducted an integrative analysis of new genome data from bat Sarbecovirus strains reported after the COVID-19 outbreak. The primary results included the identification of BANAL-20-52, Rp22DB159, and S18CXBatR24 as three close relatives of SARS-CoV-2 and the successful detection of seven out of nine key genomic features (designated as RC0-7 and ORF8) observed in wild types of SARS-CoV-2 in the three close relatives from Laos, Vietnam, and Yunnan province of China, respectively. The most significant contribution of the present study lies in the detection of RC1 in wild genotype in a bat Sarbecovirus population BANAL-20-52 belonging to. Encoding a segment of the NSP3 protein, RC1 was discovered as the second crucial clue for the origin tracing of SARS-CoV-2. Although RC0, encoding the junction furin cleavage site, remains undetected outside of the SARS-CoV-2 genome, Feuang of Laos is the sole place where eight of the nine wild-type features (RC1-7 and ORF8) have been detected.

Numerical simulation of transient boiling and void cross flow in non-uniformly heated 5 × 5 rod bundle

A multi-dimensional numerical simulation has been conducted for a transient boiling experiment by applying rapid and non-uniform power to fluid in a 5×5 bundle channel simulated a BWR fuel assembly in atmospheric pressure. The experiment is to investigate thermal hydraulic behavior in applying transient power to subcooled reactor coolant in a stand-by mode of a nuclear power plant such as reactivity initiated accident (RIA). The numerical simulation has been conducted by TRACE (version 5.0 / patch 5) which is a nuclear system analysis code to solve thermal hydraulics of boiling two phase flow by a two fluid model. The bundle channel in the upward vertical direction has been simulated by a three dimensional component with the Cartesian coordinate system attaching heat structures to simulate heating rods for thermal conduction and heat transfer calculation. It has been revealed that the numerical result is possible to simulate the void cross flow through the sub-channel in the bundle channel qualitatively as observed in the experiment. However, there was room for improvement for a wall heat transfer model in TRACE because the numerical result is larger than the experimental result in terms of the rising rate of the rod temperature during the rapid initial increasing of applied power, and it has been inferred that the evaluation model for an onset of nucleate boiling in TRACE also has to be improved because the void initiation time in the numerical result was earlier than the experimental result. Therefore, TRACE has been optimized by modifying the two physical models described above. The numerical results with the modified TRACE have been in better agreement with the experimental results than those with the original TRACE. Using the modified TRACE, a numerical experiment has been conducted putting an inlet velocity and subcooling of fluid and applied power as parameters in addition to the experimental conditions. The results have shown that there is a square law correlation between a void cross flow and applied power to the fluid. The experiments and analyses in this study have elucidated the behavior of transient boiling two phase flow in a fuel assembly of a nuclear power plant at the transient event such as RIA.

An Odor Trace Visualization System Using a Two-Dimensional Backside Scattering Localized Surface Plasmon Resonance Gas Sensor

Odor information fills every corner of our lives yet obtaining its spatiotemporal distribution is a difficult challenge. Localized surface plasmon resonance has shown good sensitivity and a high response/recovery speed in odor sensing and converts chemical information such as odor information into optical information, which can be captured by charge-coupled device cameras. This suggests that the utilization of localized surface plasmon resonance has great potential in two-dimensional odor trace visualization. In this study, we developed a two-dimensional imaging system based on backside scattering from a localized surface plasmon resonance substrate to visualize odor traces, providing an intuitive representation of the spatiotemporal distribution of odor, and evaluated the performance of the system. In comparative experiments, we observed distinct differences between odor traces and disturbances caused by environmental factors in differential images. In addition, we noted changes in intensity at positions corresponding to the odor traces. Furthermore, for indoor experiments, we developed a method of finding the optimal capture time by comparing changes in differential images relative to the shape of the original odor trace. This method is expected to assist in the collection of spatial information of unknown odor traces in future research.

Origin tracing and adulteration identification of bird's nest by high- and low-field NMR combined with pattern recognition

Edible bird’s nest (EBN) is a high-value health food with various nutrients and bioactive components. With increasing demand for EBN, they are often adulterated with cheaper ingredients or falsely labeled by the origin information, thus harming consumer interests. In this study, high- and low-field nuclear magnetic resonance (HF/LF-NMR) technology combined with multivariate statistical analysis was used to identify the geographical marker of EBN from different origins and authenticate the adulterated EBN with various adulterants at different adulteration rates. Authentic EBN samples from Malaysia were used to simulate adulteration using gelatin (GL), agar (AG) and starch (ST) at 10 %, 20 %, 40 %, 60 %, 80 %, and 100 % w/w, respectively. The results showed significant differences in composition among EBN from different origins, with isocaproate and citric acid serving as geographical markers for Malaysia and Vietnam, respectively. Leucine, glutamic acid, and N-acetylglycoprotein serving as geographical markers for Indonesia. In addition, PLS model further verified the accuracy of origin identification of EBN. The LF-NMR results of adulteration EBN showed a linear correlation between the transverse relaxation (T2, S2) and the adulterated ratio. The OPLS-DA based on T2 spectra could accurately identify authentic EBN from adulterated with GL, AG and ST at 40 %, 20 %, and 20 %, respectively. Fisher discrimination model was able to differentiate at 20 %, 20 %, and 40 %, respectively. These results show that the 1H NMR combined with multivariate statistical analysis method could be a potential tool for the detection of origin and adulteration of EBN.

The hippocampal FTO-BDNF-TrkB pathway is required for novel object recognition memory reconsolidation in mice

Memory reconsolidation refers to the process by which the consolidated memory was restored after reactivation (RA). Memory trace becomes labile after reactivation and inhibition of memory reconsolidation may disrupt or update the original memory trace, which provided a new strategy for the treatment of several psychiatric diseases, such as drug addiction and post-traumatic stress disorder. Fat mass and obesity-associated gene (FTO) is a novel demethylase of N6-methyladenosine (m6A) and it has been intensively involved in learning and memory. However, the role of FTO in memory reconsolidation has not been determined. In the present study, the function of FTO in memory reconsolidation was investigated in the novel object recognition (NOR) model in mice. The results showed that RA of NOR memory increased hippocampal FTO expression in a time-dependent manner, while FTO inhibitor meclofenamic acid (MA) injected immediately, but not 6 h after RA disrupted NOR memory reconsolidation. MA downregulated BDNF expression during NOR memory reconsolidation in the hippocampus, while the TrkB agonist 7,8-Dihydroxyflavone (7,8-DHF) reversed the disruptive effects of MA on NOR memory reconsolidation. Furthermore, overexpression of FTO increased BDNF expression via decreasing mRNA m6A in HT22 cells. Taken together, these results indicate that FTO may up-regulate the BDNF-TrkB pathway to promote NOR memory reconsolidation through m6A modification.

Trace-wise coherent noise suppression via a self-supervised blind-trace deep-learning scheme

Seismic data denoising via supervised deep learning is effective and popular but requires noise-free labels, which are rarely available. Blind-spot networks circumvent this requirement by training directly on noisy data and have been demonstrated to be a powerful suppressor of random noise. In this work, we expand the methodology of blind-spot networks to create a blind-trace network that successfully removes trace-wise coherent noise. An extensive synthetic analysis illustrates the denoising procedure’s robustness to varying noise levels and varying numbers of noisy traces within shot gathers. It is demonstrated that the network can accurately learn to suppress the noise when up to 60% of the original traces are noisy. Furthermore, our procedure is implemented on the Stratton 3D field data set and demonstrates the restoration of the previously corrupted direct arrivals. In addition to trace-wise noise suppression, we adapt the blind-spot networks to the successful suppression of colored Gaussian noise, which exhibits varying coherent properties in time and spatial axes. Our adaptation of the blind-spot networks paves the way for its use in other applications, such as the suppression of coherent noise arising from wellsite activity, passing vessels, or nearby industrial activity.

Combining unsupervised deep learning and Monte Carlo dropout for seismic data reconstruction and its uncertainty quantification

Many methods, such as multichannel singular spectrum analysis (MSSA) and deep seismic prior (DSP), have been developed for seismic data reconstruction, but they do not quantify the uncertainty of reconstructed traces, relying on the subjective visual inspection of results. Our goal is to quantify the reconstructed uncertainty while recovering missing traces. We develop a framework including an unsupervised deep-learning-based seismic data reconstruction method and the existing Monte Carlo dropout method to achieve this goal. The only information required by our framework is the original incomplete data. A convolutional neural network trained on the original nonmissing traces can simultaneously denoise and reconstruct seismic data. For uncertainty quantification, the Monte Carlo dropout method treats the well-known dropout technique as Bayesian variational inference. This refers to the fact that the dropout technique can be regarded as an approximation to the probabilistic Gaussian process and thus can be used to obtain an approximate distribution (Bernoulli variational distribution) of the posterior distribution. The reconstructed result and uncertainty of the trained model are yielded through multiple Monte Carlo dropout simulations. The analysis of the reconstructed uncertainty quantifies the confidence to use reconstructed traces. Tests on synthetic and field data illustrate that our framework outperforms the MSSA and DSP methods on reconstructed accuracy and quantifies the reconstructed uncertainty as an objective benchmark to guide decision making.

Cancer origin tracing and timing in two high-risk prostate cancers using multisample whole genome analysis: prospects for personalized medicine

BackgroundProstate cancer (PrCa) genomic heterogeneity causes resistance to therapies such as androgen deprivation. Such heterogeneity can be deciphered in the context of evolutionary principles, but current clinical trials do not include evolution as an essential feature. Whether or not analysis of genomic data in an evolutionary context in primary prostate cancer can provide unique added value in the research and clinical domains remains an open question.MethodsWe used novel processing techniques to obtain whole genome data together with 3D anatomic and histomorphologic analysis in two men (GP5 and GP12) with high-risk PrCa undergoing radical prostatectomy. A total of 22 whole genome-sequenced sites (16 primary cancer foci and 6 lymph node metastatic) were analyzed using evolutionary reconstruction tools and spatio-evolutionary models. Probability models were used to trace spatial and chronological origins of the primary tumor and metastases, chart their genetic drivers, and distinguish metastatic and non-metastatic subclones.ResultsIn patient GP5, CDK12 inactivation was among the first mutations, leading to a PrCa tandem duplicator phenotype and initiating the cancer around age 50, followed by rapid cancer evolution after age 57, and metastasis around age 59, 5 years prior to prostatectomy. In patient GP12, accelerated cancer progression was detected after age 54, and metastasis occurred around age 56, 3 years prior to prostatectomy. Multiple metastasis-originating events were identified in each patient and tracked anatomically. Metastasis from prostate to lymph nodes occurred strictly ipsilaterally in all 12 detected events. In this pilot, metastatic subclone content analysis appears to substantially enhance the identification of key drivers. Evolutionary analysis’ potential impact on therapy selection appears positive in these pilot cases.ConclusionsPrCa evolutionary analysis allows tracking of anatomic site of origin, timing of cancer origin and spread, and distinction of metastatic-capable from non-metastatic subclones. This enables better identification of actionable targets for therapy. If extended to larger cohorts, it appears likely that similar analyses could add substantial biological insight and clinically relevant value.

A comprehensive dataset of animal-associated sarbecoviruses

Zoonotic spillover of sarbecoviruses (SarbeCoVs) from non-human animals to humans under natural conditions has led to two large-scale pandemics, the severe acute respiratory syndrome (SARS) pandemic in 2003 and the ongoing COVID-19 pandemic. Knowledge of the genetic diversity, geographical distribution, and host specificity of SarbeCoVs is therefore of interest for pandemic surveillance and origin tracing of SARS-CoV and SARS-CoV-2. This study presents a comprehensive repository of publicly available animal-associated SarbeCoVs, covering 1,535 viruses identified from 63 animal species distributed in 43 countries worldwide (as of February 14,2023). Relevant meta-information, such as host species, sampling time and location, was manually curated and included in the dataset to facilitate further research on the potential patterns of viral diversity and ecological characteristics. In addition, the dataset also provides well-annotated sequence sets of receptor-binding domains (RBDs) and receptor-binding motifs (RBMs) for the scientific community to highlight the potential determinants of successful cross-species transmission that could be aid in risk estimation and strategic design for future emerging infectious disease control and prevention.

COPS: An improved information retrieval-based bug localization technique using context-aware program simplification

Information Retrieval Based Bug Localization (IRBL) techniques are well suited for large-scale software debugging with fewer external dependencies and lower execution costs. However, existing IRBL techniques have several challenges, including localization granularity and applicability. First, existing IRBL techniques have not yet achieved statement-level bug localization. Second, almost all studies are limited to Java-based projects, while their effectiveness for other popular programming languages (e.g., Python) is unknown. The reason for these deficiencies is that existing IRBL techniques mainly rely on conventional NLP techniques to analyze the bug reports and have not yet fully utilized the stack traces attached to the bug reports. To improve the IRBL technique, we propose a context-aware program simplification technique – COPS – that can localize defective statements in suspicious files by analyzing the stack traces in bug reports, enabling statement-level bug localization for Python-based projects. Our experiment is based on 948 bug reports, and the results show that COPS can effectively localize buggy statements. First, compared to the original stack traces, Top@10 is improved by 102.6%, MAP@10 by 56.2%, and MRR@10 by 95.6%. We found that actual buggy code entities are more likely to appear in the first five frames of the stack trace. Second, COPS can achieve equally good localization performance compared to state-of-the-art statement-level bug localization techniques and achieve 92% buggy statement coverage with a full-scope search. Finally, experiments found that the stack trace’s first two-thirds of information is more conducive to localizing buggy statements.

Single hybrid population but multiple parental individuals at the origin of parthenogenetic rock lizards Darevskia sapphirina and D. bendimahiensis Schmidtler, & Eiselt Darevsky (1994) endemic to the area of Lake Van in East Turkey

Among vertebrates, obligate parthenogenesis is only found in Squamata, where it always has a hybrid origin and a few lizard genera contain most of the known hybridogenous parthenogenetic taxa. Parthenogenesis thus seems to be pre-conditioned at the genus level, but it is not clear how often the encounter between two parental sexually reproducing species can result in the parthenogenetic offspring, nor whether the success of such hybridization event requires certain conditions or the specific time frame. To address this question, we studied the rock lizards of genus Darevskia, where a pair of parental species, D. valentini and D. raddei, as well as their parthenogenetic daughter species D. bendimahiensis and D. sapphirina, are found in close proximity NE of the Lake Van in East Anatolia. Using ddRAD-seq genotyping on 19 parental and 18 hybrid individuals, we found that (i) all parthenogenetic individuals from both D. bendimahiensis and D. sapphirina have a monophyletic origin tracing back to a single initial hybrid population, but their current genetic variation is geographically structured; (ii) unlike the most probable paternal ancestor, the genetically closest extant population of the maternal ancestor is not the geographically nearest one; and (iii) in the parthenogens, about 1% of loci carry multiple haplotypes, frequently differentiated by multiple substitutions. This pattern, in addition to biases in the relative frequency of haplotypes of maternal and paternal origin, does not appear compatible with a scenario of the entire parthenogenic clonal population having descended from a single pair of parental individuals. Instead, the data suggest that multiple parental individual ancestries still persist in the parthenogenetic gene pool. This supports the notion that although hybridization leading to parthenogenesis is generally rare at the level of species, it may be more common at the individual/population level once the right conditions are met.

Modern Approaches to Criminalistic Identification: The Role of Genomic Identification

Criminalistic identification is an important instrument in the investigation of crimes. The article analyzes the classification of identification methods with an emphasis on genomic identification. The importance of applying modern methods of genomic identification in criminalistics is stressed, the problems associated with the collection of specimens for comparative research are studied, and the requirements to the collection of traces of biological origin are described. The author presents a review of publications and current research methods in the field of criminalistic identification. A classification of criminalistic identification based on different criteria is given, including the criteria of legal nature, type of reflection, evidential significance and properties of identified objects. Key methods of genomic identification, such as the polymerase chain reaction (PCR), microsatellite analysis, DNA sequencing and others are examined within the context of their application in criminalistics. The author presents the results of analyzing the existing methods of genomic identification and the problems connected with specimen collection. The requirements to the collection of traces of biological origin are identified. However, it is considered impossible to offer a universal algorithm of identifying, collecting and preserving biological evidence. The analysis of the results allows the author to draw conclusions about the importance of genomic identification in criminalistics and the necessity of observing requirements to collecting the traces of biological origin.

Study on physicochemical properties, fatty acids, texture, antioxidant and antibacterial activities of ghee from different regions

Due to the lack of basic information on Chinese ghee and the increasing demand of consumers for natural oils, this study aims to explore and distinguish the quality characteristics of ghee in different regions of China. Ghee samples from 16 regions of Qinghai Province, Gansu Province, Xinjiang Uyghur Autonomous Region, and Tibet Autonomous Region were selected and their physicochemical properties, fatty acids, texture, antioxidant and antibacterial activities were determined. The results showed that: (1) The physicochemical properties of ghee were different from different regions, but the freshness and fat content are generally high. The results of iodine value and saponification value suggest that the fatty acid composition is good; (2) The unsaturated fatty acid/saturated fatty acid content of ghee in Tibet and Xinjiang ranges from 63.05% to 79.13%, which is better than that in other regions; (3) Gansu Diebu ghee has the highest hardness (40.69 N); (4) Ghee from different regions has good antioxidant activity, DPPH free radical scavenging activity is 30.45% to 58.06%, ABTS free radical scavenging activity is 41.14% to 65.53%, and has varying degrees of inhibition on gram-positive bacteria. In addition, yak ghee, cattle-yak ghee and cow ghee have better fatty acid composition and antibacterial ability than scalper ghee. The results of this study distinguish the differences in the quality characteristics of yak ghee in different geographical regions. Therefore, it can provide a theoretical basis for the origin tracing and quality-oriented improvement of yak ghee.