A brief review of forensically important flesh flies (Diptera: Sarcophagidae)

Forensic entomology could provide valuable data for the minimum postmortem interval (PMImin) estimation and other relevant information,such as causes and circumstances of death.Some representatives of flesh flies are one of the dominant necrophagous insects during early stages of decomposition,demonstrating unique biological characteristics compared with other necrophagous flies.Moreover,they lead to global health concerns as carriers of various pathogenic micro-organisms,and dominantly result in the traumatic myiasis.Thus,sarcophagid flies are considered important in decomposition processes for PMImin estimation.However,the utility of sarcophagid flies has been seriously hampered by limited ecological,biological and taxonomic knowledge of them.The aim of this paper is to provide a brief review on the species,distribution and biological habit of forensically important sarcophagid flies.In addition,the relation between traumatic myiasis and flesh flies,molecular identification methods and developmental pattern of flesh flies are summarized.

Identification of forensically important blow fly species （Diptera： Calliphoridae） in China by mitochondrial cytochrome oxidase I gene differentiation

Unambiguous and rapid sarcosaphagous insect species identification is an essential requirement for forensic investigations. Although some insect species are difficult to classify morphologically, they can be effectively identified using molecular methods based on similarity with abundant authenticated reference DNA sequences in local databases. However, local databases are still relatively incomplete in China because of the large land area with distinct regional conditions. In this study, 75 forensically important blow flies were collected from 23 locations in 16 Chinese provinces, and a 278-bp segment of the cytochrome oxidase subunit I gene of all specimens was successfully sequenced. Phylogenetic analysis of the sequenced segments showed that all Calliphorid specimens were properly assigned into nine species with relatively strong supporting values, thus indicating that the 278-bp cytochrome oxidase subunit one region is suitable for identification of Calliphorid species. The clear difference between intraspecific threshold and interspecific divergence confirmed the potential of this region for Calliphorid species identification, especially for distinguishing between morphologically similar species. Intraspecific geographic variations were observed in Lucilia sericata （Meigen, 1826） and Lucilia caesar （Linnaeus, 1758）.

Molecular identification of the potentially forensically relevant cluster flies Pollenia rudis (Fabricius) and Pollenia vagabunda (Meigen) (Diptera: Polleniidae) — non-recorded species in Algeria

Cluster flies are represented by the genus Pollenia Robineau-Desvoidy,1830 of the family Polleniidae Brauer and Bergenstamm,1889.Their larvae are known to be internal parasites or predators of earthworms.Herein,we report for the first time the occurrence of the cluster flies Pollenia rudis Fabricius,1794 and Pollenia vagabunda(Meigen,1826)(Diptera:Polleniidae)on carcasses in Algeria and identify them through DNA barcoding.A region of the mitochondrial cytochrome c oxidase I gene(COI)was amplified and sequenced.Genetic distances were determined.A phylogenetic tree was constructed with the maximum parsimony method using 10000 bootstrap replicates.A total number of 157 adults of P.rudis were collected together with 325 adults of Pollenia vagabunda.The occurrence of Pollenia on animal carcasses does not seem to be correlated with a particular stage of decomposition.All the sequences were correctly identified using the BLASTn tool from the GenBank database and the BOLD identification engine.Intra-and interspecific sequence divergence values were less than 1%and greater than 3%,respectively.COI barcodes obtained from this study were robust enough to identify and distinguish unambiguously between P.rudis and P.vagabunda.In the tree-based analysis,the cluster flies were all assigned to their respective species separately from each other confirming the morphological identification.These results provide DNA barcodes that contribute to the growth of reference databases and allow fast and accurate identification.

Metrological framework for selecting morphological characters to identify species and estimate developmental maturity of forensically significant insect specimens

Accurate age estimates of immature necrophagous insects associated with a human or animal body can provide evidence of how long the body has been dead.These estimates are based on species-specific details of the insects’aging processes,and therefore require accurate species identification and developmental stage estimation.Many professionals who produce or use identified organisms as forensic evidence have little training in taxonomy or metrology,and appreciate the availability of formalized principles and standards for biological identification.Taxonomic identifications are usually most readily and economically made using categorical and qualitative morphological characters,but it may be necessary to use less convenient and potentially more ambiguous characters that are continuous and quantitative if two candidate species are closely related,or if identifying developmental stages within a species.Characters should be selected by criteria such as taxonomic specificity and metrological repeatability and relative error.We propose such a hierarchical framework,critique various measurements of immature insects,and suggest some standard approaches to determine the reliability of organismal identifications and measurements in estimating postmortem intervals.Relevant criteria for good characters include high repeatability(including low scope for ambiguity or parallax effects),pronounced discreteness,and small relative error in measurements.These same principles apply to individuation of unique objects in general.

Mitochondrial and Nuclear DNA-based Identification of Some Forensically Important Calliphoridae(Diptera)in Luoyang of China

Introduction:Calliphoridae plays a key role in forensic entomology research,which is one of the first insects to decompose animal carcasses.The mitochondrial cytochrome c oxidase subunit I and the ribosomal internal transcribed spacer 2(ITS2)are among the most widely used molecular markers for insect taxonomic characterization.Aim:The aim of the study was to test the suitability of two genetic markers based on conducting the molecular identification of six necrophagous Calliphorid flies.Materials and Methods:Fourteen Calliphoridae flies were collected and classified with traditional morphological characteristics.The DNA of flies was extracted and the fragments of COI and ITS2 were amplified and sequenced.All the sequences were aligned and analyzed by MEGA 7 software for NCBI BLAST,nucleotide composition,intra-and inter-specific divergence calculation,and phylogenetic tree inference successively.Results:The results indicated that COI and ITS2 genes were robust in the identification of Calliphoridae at the species level and ITS2 gene sequence possessed a strong resolution power as it showed higher variation values between Lucilia sericata and Lucilia cuprina,Calliphora vomitoria and Triceratopyga calliphoroides,C.vomitoria andAldrichina grahami,but inferior to COI fbrT.calliphoroides and A.grahami.Conclusions:Our results showed that combination of COI+ITS2 genes yields more accurate identification and diagnoses and better agreement with morphological data than the mitochondrial barcodes alone.As a supplementary method for morphological identification,we advocated for the combination of nuclear and mitochondrial gene approaches to address the taxonomy and phylogeny of forensic relevant flies,especially of closely related species and populations.

Factors affecting forensic electric network frequency matching-A comprehensive study

The power system frequency fluctuations could be captured by digital recordings and extracted to compare with a reference database for forensic timestamp verification.It is known as the Electric Network Frequency(ENF)criterion,enabled by the properties of random fluctuations and intra-grid consistency.In essence,this is a task of matching a short random sequence within a long reference,whose accuracy is mainly concerned with whether this match could be uniquely correct.In this paper,we comprehensively analyze the factors affecting the reliability of ENF matching,including the length of test recording,length of reference,temporal resolution,and Signal-to-Noise Ratio(SNR).For synthetic analysis,we incorporate the first-order AutoRegressive(AR)ENF model and propose an efficient Time-Frequency Domain noisy ENF synthesis method.Then,the reliability analysis schemes for both synthetic and real-world data are respectively proposed.Through a comprehensive study,we quantitatively reveal that while the SNR is an important external factor to determine whether timestamp verification is viable,the length of test recording is the most important inherent factor,followed by the length of reference.However,the temporal resolution has little impact on performance.Finally,a practical workflow of the ENF-based audio timestamp verification system is proposed,incorporating the discovered results.

An Adaptive Hate Speech Detection Approach Using Neutrosophic Neural Networks for Social Media Forensics

Detecting hate speech automatically in social media forensics has emerged as a highly challenging task due tothe complex nature of language used in such platforms. Currently, several methods exist for classifying hatespeech, but they still suffer from ambiguity when differentiating between hateful and offensive content and theyalso lack accuracy. The work suggested in this paper uses a combination of the Whale Optimization Algorithm(WOA) and Particle Swarm Optimization (PSO) to adjust the weights of two Multi-Layer Perceptron (MLPs)for neutrosophic sets classification. During the training process of the MLP, the WOA is employed to exploreand determine the optimal set of weights. The PSO algorithm adjusts the weights to optimize the performanceof the MLP as fine-tuning. Additionally, in this approach, two separate MLP models are employed. One MLPis dedicated to predicting degrees of truth membership, while the other MLP focuses on predicting degrees offalse membership. The difference between these memberships quantifies uncertainty, indicating the degree ofindeterminacy in predictions. The experimental results indicate the superior performance of our model comparedto previous work when evaluated on the Davidson dataset.

Predicting Age and Gender in Author Profiling: A Multi-Feature Exploration

Author Profiling (AP) is a subsection of digital forensics that focuses on the detection of the author’s personalinformation, such as age, gender, occupation, and education, based on various linguistic features, e.g., stylistic,semantic, and syntactic. The importance of AP lies in various fields, including forensics, security, medicine, andmarketing. In previous studies, many works have been done using different languages, e.g., English, Arabic, French,etc.However, the research on RomanUrdu is not up to the mark.Hence, this study focuses on detecting the author’sage and gender based on Roman Urdu text messages. The dataset used in this study is Fire’18-MaponSMS. Thisstudy proposed an ensemble model based on AdaBoostM1 and Random Forest (AMBRF) for AP using multiplelinguistic features that are stylistic, character-based, word-based, and sentence-based. The proposed model iscontrasted with several of the well-known models fromthe literature, including J48-Decision Tree (J48),Na飗e Bays(NB), K Nearest Neighbor (KNN), and Composite Hypercube on Random Projection (CHIRP), NB-Updatable,RF, and AdaboostM1. The overall outcome shows the better performance of the proposed AdaboostM1 withRandom Forest (ABMRF) with an accuracy of 54.2857% for age prediction and 71.1429% for gender predictioncalculated on stylistic features. Regarding word-based features, age and gender were considered in 50.5714% and60%, respectively. On the other hand, KNN and CHIRP show the weakest performance using all the linguisticfeatures for age and gender prediction.

IMTNet:Improved Multi-Task Copy-Move Forgery Detection Network with Feature Decoupling and Multi-Feature Pyramid

Copy-Move Forgery Detection(CMFD)is a technique that is designed to identify image tampering and locate suspicious areas.However,the practicality of the CMFD is impeded by the scarcity of datasets,inadequate quality and quantity,and a narrow range of applicable tasks.These limitations significantly restrict the capacity and applicability of CMFD.To overcome the limitations of existing methods,a novel solution called IMTNet is proposed for CMFD by employing a feature decoupling approach.Firstly,this study formulates the objective task and network relationship as an optimization problem using transfer learning.Furthermore,it thoroughly discusses and analyzes the relationship between CMFD and deep network architecture by employing ResNet-50 during the optimization solving phase.Secondly,a quantitative comparison between fine-tuning and feature decoupling is conducted to evaluate the degree of similarity between the image classification and CMFD domains by the enhanced ResNet-50.Finally,suspicious regions are localized using a feature pyramid network with bottom-up path augmentation.Experimental results demonstrate that IMTNet achieves faster convergence,shorter training times,and favorable generalization performance compared to existingmethods.Moreover,it is shown that IMTNet significantly outperforms fine-tuning based approaches in terms of accuracy and F_(1).

Source Camera Identification Algorithm Based on Multi-Scale Feature Fusion

The widespread availability of digital multimedia data has led to a new challenge in digital forensics.Traditional source camera identification algorithms usually rely on various traces in the capturing process.However,these traces have become increasingly difficult to extract due to wide availability of various image processing algorithms.Convolutional Neural Networks(CNN)-based algorithms have demonstrated good discriminative capabilities for different brands and even different models of camera devices.However,their performances is not ideal in case of distinguishing between individual devices of the same model,because cameras of the same model typically use the same optical lens,image sensor,and image processing algorithms,that result in minimal overall differences.In this paper,we propose a camera forensics algorithm based on multi-scale feature fusion to address these issues.The proposed algorithm extracts different local features from feature maps of different scales and then fuses them to obtain a comprehensive feature representation.This representation is then fed into a subsequent camera fingerprint classification network.Building upon the Swin-T network,we utilize Transformer Blocks and Graph Convolutional Network(GCN)modules to fuse multi-scale features from different stages of the backbone network.Furthermore,we conduct experiments on established datasets to demonstrate the feasibility and effectiveness of the proposed approach.

Need for education of psychiatric evaluation of offenders with mental disorders:A questionnaire survey for Japanese designated psychiatrists

BACKGROUND The management of offenders with mental disorders has been a significant concern in forensic psychiatry.In Japan,the introduction of the Medical Treatment and Supervision Act in 2005 addressed the issue.However,numerous psychiatric patients at risk of violence still find themselves subject to the administrative involuntary hospitalization(AIH)scheme,which lacks clarity and updated standards.AIM To explore current as well as optimized learning strategies for risk assessment in AIH decision making.METHODS We conducted a questionnaire survey among designated psychiatrists to explore their experiences and expectations regarding training methods for psychiatric assessments of offenders with mental disorders.RESULTS The findings of this study’s survey suggest a prevalent reliance on traditional learning approaches such as oral education and on-the-job training.CONCLUSION This underscores the pressing need for structured training protocols in AIH consultations.Moreover,feedback derived from inpatient treatment experiences is identified as a crucial element for enhancing risk assessment skills.

Evaluation of a Novel 32 X-STR Loci Multiplex System in the Forensic Application

The AGCU X Plus STR system is a newly developed multiplex PCR kit that detects 32 X-chromosomal STR loci simultaneously.These are DXS6807,DXS9895,linkage group 1(DXS10148,DXS10135,DXS8378),DXS9902,DXS6795,DXS6810,DXS10159,DXS10162,DXS10164,DXS7132,linkage group 2(DXS10079,DXS10074,DXS10075),DXS981,DXS6800,DXS6803,DXS6809,DXS6789,DXS7424,DXS101,DXS7133,GATA172D05,GATA165B12,linkage group 3(DXS10103,HPRTB,DXS10101),GATA31E08 and linkage group 4(DXS8377,DXS10134,DXS7423).A major advantage of this kit is that it takes into account linkage between loci,in addition to detecting more X-STR loci.In order to evaluate the forensic application of 32 X-STR fl uorescence amplifi cation system,PCR settings,sensitivity,species specifi city,stability,DNA mixtures,concordance,stutter,sizing precision,and population genetics investigation were evaluated according to the Scientific Working Group on DNA Analysis Methods(SWGDAM)developmental validation guidelines.The study showed that the genotyping results of each locus were signifi cantly accurate when the DNA template was at least 62.5 pg.Complete profi les were obtained for the 1∶1 and 1∶3 combinations.A total of 209 unrelated individuals from Southern Chinese Han community,consisting of 84 females and 125 males,were selected for population studies,and 285 allele profi les were detected from 32 X-STR loci.The polymorphism information content(PIC)ranged from 0.2721 in DXS6800,to 0.9105 in DXS10135,with an average of 0.6798.DXS10135(PIC=0.9105)was the most polymorphic locus,with discrimination power(DP)of 0.9164 and 0.9871 for the male and female.The cumulative PD_(F),PD_(M),MEC_(trio) and MEC_(duo) valu es were all greater than 0.999999999.There were 78 different DXS10103-HPRTB-DXS10101 haplotypes among the 125 males,and the haplotype diversity was 0.9810.There was no signifi cant difference in the cumulative PD_(F),PD_(M),MEC_(trio) and MEC_(duo) values whether considering linkage or not.In summary,the new X-STR multiplex typing system is effective and reliable,which can be useful in human genetic analysis and kinship testing as a potent complement to autosomal STR typing.

Fusion of Type-2 Neutrosophic Similarity Measure in Signatures Verification Systems: A New Forensic Document Analysis Paradigm

Signature verification involves vague situations in which a signature could resemble many reference samples ormight differ because of handwriting variances. By presenting the features and similarity score of signatures from thematching algorithm as fuzzy sets and capturing the degrees of membership, non-membership, and indeterminacy,a neutrosophic engine can significantly contribute to signature verification by addressing the inherent uncertaintiesand ambiguities present in signatures. But type-1 neutrosophic logic gives these membership functions fixed values,which could not adequately capture the various degrees of uncertainty in the characteristics of signatures. Type-1neutrosophic representation is also unable to adjust to various degrees of uncertainty. The proposed work exploresthe type-2 neutrosophic logic to enable additional flexibility and granularity in handling ambiguity, indeterminacy,and uncertainty, hence improving the accuracy of signature verification systems. Because type-2 neutrosophiclogic allows the assessment of many sources of ambiguity and conflicting information, decision-making is moreflexible. These experimental results show the possible benefits of using a type-2 neutrosophic engine for signatureverification by demonstrating its superior handling of uncertainty and variability over type-1, which eventuallyresults in more accurate False Rejection Rate (FRR) and False Acceptance Rate (FAR) verification results. In acomparison analysis using a benchmark dataset of handwritten signatures, the type-2 neutrosophic similaritymeasure yields a better accuracy rate of 98% than the type-1 95%.

Logical Image Acquisition and Analysis of Android Smartphones

Android smartphones largely dominate the smartphone market. For this reason, it is very important to examine these smartphones in terms of digital forensics since they are often used as evidence in trials. It is possible to acquire a physical or logical image of these devices. Acquiring physical and logical images has advantages and disadvantages compared to each other. Creating the logical image is done at the file system level. Analysis can be made on this logical image. Both logical image acquisition and analysis of the image can be done by software tools. In this study, the differences between logical image and physical image acquisition in Android smartphones, their advantages and disadvantages compared to each other, the difficulties that may be encountered in obtaining physical images, which type of image contributes to obtaining more useful and effective data, which one should be preferred for different conditions, and the benefits of having root authority are discussed. The practice of getting the logical image of the Android smartphones and making an analysis on the image is also included. Although root privileges are not required for logical image acquisition, it has been observed that very limited data will be obtained with the logical image created without root privileges. Nevertheless, logical image acquisition has advantages too against physical image acquisition.

Research on Electronic Forensics Based on Blockchain Technology

The development of high technology,for public life to provide a justification at the same time,also encouraged the spirit of cybercrime,to become more and more rampant.In network crime,electronic data is usually used as the main evidence to determine the facts of the crime and plays an important role in the smooth trial of the case.But because electronic data on dependent,concealment,easy destructive strong science and technology,the forensics work is now in trouble.The mature use of blockchain technology can avoid existing problems to a certain extent,which is helpful to the smooth progress of electronic forensics.This paper on electronic evidence how to more effectively,combined with research blockchain technology,improve the efficiency of electronic evidence collection work.

Ending Privacy’s Gremlin: Stopping the Data-Broker Loophole to the Fourth Amendment’s Search Warrant Requirement

Advances in technology require upgrades in the law. One such area involves data brokers, which have thus far gone unregulated. Data brokers use artificial intelligence to aggregate information into data profiles about individual Americans derived from consumer use of the internet and connected devices. Data profiles are then sold for profit. Government investigators use a legal loophole to purchase this data instead of obtaining a search warrant, which the Fourth Amendment would otherwise require. Consumers have lacked a reasonable means to fight or correct the information data brokers collect. Americans may not even be aware of the risks of data aggregation, which upends the test of reasonable expectations used in a search warrant analysis. Data aggregation should be controlled and regulated, which is the direction some privacy laws take. Legislatures must step forward to safeguard against shadowy data-profiling practices, whether abroad or at home. In the meantime, courts can modify their search warrant analysis by including data privacy principles.

Eye on the Sky: A UAP Research and Field Study off New York’s Long Island Coast

A ten-month field research study was meticulously conducted at Robert Moses State Park (RMSP) on the south shore of Long Island, NY. The objective was to determine if aerial phenomena of an unknown nature exist over a coastal location and to characterize their properties and behaviors. Primary and secondary field observation methods were utilized in this data-centric study. Forensic engineering principles and methodologies guided the study. The challenges set forward were object detection, observation, and characterization, where multispectral electro-optical devices and radar were employed due to limited visual acuity and intermittent presentation of the phenomena. The primary means of detection utilized a 3 cm X-band radar operating in two scan geometries, the X- and Y-axis. Multispectral electro-optical devices were utilized as a secondary means of detection and identification. Data was emphasized using HF and LF detectors and spectrum analyzers incorporating EM, ultrasonic, magnetic, and RF field transducers to record spectral data in these domains. Data collection concentrated on characterizing VIS, NIR, SWIR, LWIR, UVA, UVB, UVC, and the higher energy spectral range of ionizing radiation (alpha, beta, gamma, and X-ray) recorded by Geiger-Müller counters as well as special purpose semiconductor diode sensors.

Web数字取证系统的研究与实现

通过对当前信息安全的分析,数字取证已成为信息安全和司法领域的研究热点.文中在分析现有Web攻击的基础上,综合利用基于主机和网络的入侵检测技术,开发出一套高效实用的Web数字取证系统.该系统通过取证代理不断监视和分析网络中对Web服务器的访问情况,在保护Web服务器安全的基础上,确定网络入侵者的行为是否已构成犯罪,然后提取和分析入侵犯罪信息,实现证据信息的完整性保护,同时通过对证据进行融合,生成入侵犯罪证据.

134例眼损伤法医学鉴定统计分析

眼损伤在活体法医学鉴定中比较常见,居第4位鉴于国内眼损伤法医学鉴定文献较少,现将我室几年来所鉴定的134例眼损伤的统计资料报告如下:材料和方法本文所报告的134例眼损伤,为1984年11月至1988年10月我室受理的眼损伤鉴定案例.全部材料均根据伤后病志和鉴定时的检查所见及鉴定结论列表,进行统计分析.

对罚金刑适用的思考

对罚金刑适用的思考廖燕谋，石琪琪当前，我国适用罚金刑的案件还不多。原因是法院一方面考虑到立法上的不确定性，另一方面，在长期审判实践中很少适用罚金刑，因而法院更愿意适用于其他的刑种来替代。但在经济发展的情况下，经济犯罪、法人犯罪日益增多，罚金作为一种重...