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Documentation and Preservation of the Evidences and Reconstruction of A Crime Scene using Augmented Reality, Virtual Reality and Synthetic Reality: Introducing Crime Scene DPR System Bringing the Jury to the Crime Scene
A crime scene, which is the place where a crime has occurred, is suspected of having been committed, or where evidence of a crime has been found, is an essential part of an investigation because it contains all the important details related to the crime. A careful examination of the crime scene can reveal the potential modus operandi of the criminal and establish the Corpus Delicti in court. The first visit to a crime scene is the investigator’s most crucial and often only real opportunity to observe, record, collect, and preserve evidence in its original state. Any subsequent visit holds little to no value, as the scene is usually disturbed, compromised, or altered, either intentionally or unintentionally. Thus, recording a crime became an extremely important step. The typical ways of documenting the crime scene only allow us to view the documents physically; we are unable to provide a visual or allow us to walk to the real crime scene. To help with the investigation, it is crucial to take pictures of the crime scene and any possible evidence. Virtual reality and augmented reality are in high demand right now. Whereas Augmented Reality incorporates a real-world background, Virtual Reality presents an entirely virtualized version of the situation. Virtual reality (VR) is a kind of
Forensic Unraveling the Unique: Investigating Peculiarities in Different Signature Styles
Background: Every individual owns their specific style of doing the act of writing. The style is an acquired skill that grows during the learning process through the related environment. Nowadays, it has become common for white-collar crime offenders to deliberately incorporate different styles for their illegal benefit in writing, which gives the effect of execution by more than one author. Handwriting and signature identification have always been the primary part of the forensic examination of questioned documents. These types of distinct signatures always hold major complexity in their examination and can be confusing with the outcome of different authors, especially if a similar style has not been incorporated into the standard exhibits. As such, it has become a challenge for the forensic questioned document examiner to achieve that level of expertise where, despite adopting different styles, the author could easily be identified. Aim: So, this paper aims for an examination of the signatures engaged by the same individual who executes the signatures distinctively on every occasion and shows that they are executed by the same person. Objectives: To achieve this, a thorough examination was conducted. Material: handwriting characteristics were studied using the hand magnifier, protector, and a dimension scale. Result: which is helpful for forensic questioned document experts in forming a conclusive opinion, especially when exhibits of similar models and designs are not available. Conclusion: It is concluded that a detailed examination can lead to the common authorship, despite adopting different styles
Analysis of Handwriting of Juveniles in Conflict with the Law: An Insight into Forensic Psychology
Context: The rise in juvenile delinquency in India highlights the need for alternative methods of profiling. Graphology provides a non-invasive way to examine behavioral and emotional characteristics by analyzing handwriting. Aims: To examine the handwriting of juveniles in conflict with the law and identify psychological and behavioral indicators that may aid in forensic profiling and rehabilitation efforts. Settings and Design: A cross-sectional observational study conducted at observation homes in Prayagraj, Mirzapur, and Chitrakoot, Uttar Pradesh, involving juveniles aged 12 to 18 years. Methods and Material: Handwriting samples from 100 juveniles were assessed based on ten parameters: Slant, Baseline, Margins, Spacing, Pen Pressure, Size, Speed, Zones, Letter Formation, and Connecting Strokes. Interpretations were drawn from established graphological frameworks. Statistical analysis used: Descriptive statistics and frequency distributions were used to identify prominent handwriting features and their association with behavioral traits. Results: Inclined slants (43.3%), descending baselines (43.3%), and heavy pen pressure (76.3%) were commonly observed, correlating with emotional suppression, disillusionment, and assertiveness. Spacing patterns and zone emphasis suggested issues with trust and ambition, while slow writing speed (81.4%) indicated passivity
Drug-facilitated Crimes: A Review of the Spectrum of Drugs Involved in Drug-facilitated Crimes
Drugs can alter a victim’s perception and decision-making. Drug-facilitated crimes (DFCs) include drug-facilitated sexual assault (DFSA), robbery, murder, and drug trafficking. These drugs are typically disguised in alcoholic and non-alcoholic beverages and food and the majority of the cases included powerful central nervous system depressants. Drugs utilised in sexual assaults are frequently distributed at raves, dance clubs, and bars, but they are also being promoted at private gatherings. Pharmaceutical drugs, including benzodiazepines and their derivatives (such as zolpidem, zopiclone, or zaleplon), are implicated in over 60% of cases of DFC. Among these drugs, clonazepam (26%), zolpidem (16%), bromazepam (15%), histamine antagonists (8.2%), neuroleptics (3.9%), and anesthetics (specifically GHB and ketamine, which collectively account for 2.8% of the cases) are commonly employed in DFCS. This article aims to offer a comprehensive examination of the substances frequently employed to facilitate criminal behavior, together with an exploration of their underlying mechanisms of action.
Enhancing Forensic Processes with Quantum Cryptographic Techniques: A Comprehensive Investigation
Every day, forensic investigators find themselves buried under an avalanche of digital evidence, terabytes of files, logs, and signals that can make even the most seasoned analyst feel overwhelmed. At the same time, cybercriminals are sharpening their tools, probing weaknesses in traditional encryption, and leaving us vulnerable just when we need airtight security most. Enter quantum cryptography: a radical shift in how we protect information, where the very laws of physics guard our data. Quantum Key Distribution (QKD) uses delicate photons to forge encryption keys that, if tampered with, immediately betray an eavesdropper’s presence. Alongside this, post-quantum cryptographic schemes promise software defenses that even future quantum computers can’t crack.1 In this review, we’ll walk you through how these quantum-powered techniques can transform three critical stages of forensic work: capturing evidence without fear of interception, preserving an unbreakable chain of custody, and verifying data integrity long after a case closes. You’ll learn about the nuts and bolts of QKD networks,2 the latest in quantum-resistant algorithms, and how hybrids of the two can give investigators both immediate and future-proof protection. We’ll also tackle the real-world hurdles, bulky hardware, system integration headaches, and the need for common standards, and point toward research paths and practical roadmaps that could bring quantum-secure forensics into every lab
Impact of solvent polarity on the photoinduced dynamics of a push–pull molecular motor
Light-driven rotary molecular motors convert light energy into unidirectional rotational movement. In overcrowded alkene-based molecular motors, rotary motion is accomplished through consecutive cis–trans photoisomerization reactions and thermal helix inversion steps. To date, a complete understanding of the photoisomerization reactions of overcrowded alkene motors has not been achieved yet. In this work, we use quantum chemical calculations and quantum mechanics/molecular mechanics nonadiabatic dynamics simulations to investigate the photoinduced dynamics of a push–pull alkene-based molecular motor in two different solvents: cyclohexane and methanol. We show that, while in both solvents the main photorelaxation pathway of our investigated push–pull motor involves two different excited-state minima, in polar methanol, the photorelaxation dynamics is much faster than in nonpolar cyclohexane because of two main effects: (i) a lowering of the energy barrier between the excited-state minima and (ii) a reduction in the energy gap with the ground state at the largely twisted dark minimum, where the excited-state decay takes place. Both effects can be attributed to solvent-polarity stabilization of the charge-transfer excited state along the photorelaxation pathway. In line with the experimental findings, our simulations also indicate that, in methanol, the accelerated photoinduced dynamics goes along with a faster fluorescence decay and a large reduction in the forward photoisomerization yield of our investigated motor.
Single file dynamics of tethered random walkers
We consider the single file dynamics of N identical random walkers moving with diffusivity D in one dimension (walkers bounce off each other when attempting to overtake). In addition, we require that the separation between neighboring walkers does not exceed a threshold value Δ and therefore call them “tethered walkers” (they behave as if bounded by strings that fully tighten when reaching the maximum length Δ). For a finite Δ, we study the diffusional relaxation to the equilibrium state and characterize the latter [the long-time relaxation is exponential with a characteristic time that scales as (NΔ)2/D]. In particular, our approximate approach for the N-particle probability distribution yields the one-particle distribution function of the central and edge particles (the first two positional moments are given as power expansions in Δ/4Dt). For N = 2, we find an exact solution (both in the continuum and on-lattice case) and use it to test our approximations for one-particle distributions, positional moments, and correlations. For finite Δ and arbitrary N, edge particles move with an effective long-time diffusivity D/N, in sharp contrast with the 1/ln(N)-behavior observed when Δ = ∞. Finally, we compute the probability distribution of the equilibrium system length and associated entropy. We find that the force required to change this length by a given amount is linear in this quantity; the (entropic) spring constant is 6kBT/(NΔ2). In this respect, the system behaves as an ideal polymer. The main analytical results are confirmed using Monte Carlo simulations.
Repeated interaction scheme for the quantum simulation of non-Markovian electron transfer dynamics
Quantum algorithms have the potential to revolutionize our understanding of open quantum systems in chemistry. In this work, we demonstrate that a repeated interaction model, which could serve as the foundation for a digital quantum algorithm, can effectively reproduce non-Markovian electron transfer dynamics under four different donor–acceptor parameter regimes and for a donor–bridge–acceptor system. We systematically explore how the model scales for the regimes. Notably, our approach exhibits favorable scaling in the required repeated interaction duration as the electronic coupling, temperature, damping rate, and system size increase. Furthermore, a single Trotter step per repeated interaction leads to an acceptably small error, and high-fidelity initial states can be prepared with a short time evolution. This efficiency highlights the potential of the model for tackling increasingly complex systems. When fault-tolerant quantum hardware becomes available, algorithms based on this model could be extended to incorporate structured baths, additional energy levels, or more intricate coupling schemes, enabling the simulation of real-world open quantum systems that remain beyond the reach of classical computation.
What is a chemostat? Insights from hybrid dynamics and stochastic thermodynamics
At the microscopic scale, open chemical reaction networks are described by stochastic reactions that follow mass-action kinetics and are coupled to chemostats. We show that closed chemical reaction networks—with specific stoichiometries imposed by mass-action kinetics—behave like open ones in the limit where the abundances of a subset of species become macroscopic, thus playing the role of chemostats. We prove that this limit is thermodynamically consistent by recovering the local detailed balance condition of open chemical reaction networks and deriving the proper expression of the entropy production rate. In particular, the entropy production rate features two contributions: one for the dissipation of the stochastic reactions and the other accounting for the dissipation of continuous reactions controlling the chemostats. Finally, we illustrate our results for two prototypical examples.
The topological way—A new methodology to construct symmetric sets of valence-bond structures
Classical valence bond (VB) theory has advanced significantly in recent years, evolving into a quantitative tool comparable to molecular orbital-based methods. A key advantage of VB is its high interpretability through Lewis-like resonance structures. However, traditional VB theory faces challenges with symmetric systems, as it often fails to generate symmetric sets of structures, leading to a loss of wavefunction interpretability. In this work, we extend the chemical insight approach and present a method for constructing symmetric VB sets. Rather than relying on conventional symmetry techniques, our method is predominantly based on topological information. It utilizes molecular geometry and connectivity and integrates scoring criteria for atoms, bonds, and structures. This approach enables the classification of VB structures into symmetry-adapted subsets guided by chemical intuition and topological features. We have successfully applied this method to a variety of molecular systems, demonstrating its ability to generate symmetric VB sets even in cases where traditional Rumer rules fail. These advancements contribute meaningfully to the interpretability of VB wavefunctions, marking a significant step forward in the development of VB theory.
Variational functional in local density approximation for coulombic electrolyte correlations in the electric double layer
A classical coulombic correlation functional in one-loop (1L) and local-density-approximation (LDA) is derived for electrolyte solutions, starting from a first-principles many-body partition function. The 1L–LDA functional captures correlations between electrolyte ions and solvent dipoles, such as screening and solvation, which are ignored by conventional mean-field theories. This 1L–LDA functional introduces two parameters that can be tuned to the experimental dielectric permittivity and activity coefficients in the bulk electrolyte solution. The capabilities of the 1L–LDA functional for the description of metal–electrolyte interfaces are demonstrated by embedding the functional into a combined quantum–classical model. Here, the 1L–LDA functional leads to a more pronounced double-peak structure of the interfacial capacitance with higher peaks and shorter peak-to-peak distance, significantly improving the agreement with experimental data and showing that electrolyte correlation effects exert a vital impact on the capacitive response.
Excited-state decay dynamics of endohedral metal–metal-bonding fullerenes
Endohedral metal–metal-bonding fullerenes, in which the endohedral metal atoms form covalent metal–metal bonds, are typical models for studying the confined metal–metal bonds. Herein, utilizing time-dependent ab initio nonadiabatic dynamic simulations, we explore the electron excited-state decay dynamics in endohedral metal–metal-bonding fullerenes M2@C82 (M = Sc, Y, La). The calculation results revealed that the electron relaxation time decreases with initial excited energy, with saturation occurring for excess energies starting from 2.1 eV. Y2@C82 exhibits a significantly longer electron decay time compared to Sc2@C82 and La2@C82. The reasons are attributed to the unique electronic structure and dynamics associated with the Y atoms, which modify the density of states and impact motion. Those findings enhance our understanding of the intricate dynamics within endohedral fullerenes and highlight the importance of metal elements in tailoring their physical properties for advanced applications.
Non-adiabatic dynamics simulations reveal the reversal of photoinduced electron transfer in zinc phthalocyanine/endohedral metallofullerene donor–acceptor complexes via substitution and solvent effects
Herein, we investigated the photoinduced dynamics of a zinc phthalocyanine N-pyridyl-substituted Sc3N@Ih-C80 (ZnPc-C80) donor–acceptor complex and its sulfonyl-substituted derivative ZnPcS-C80 with static electronic structure calculations and non-adiabatic dynamics simulations. We found that despite the similar geometric structures, the introduction of substituents significantly changes their electronic structures and leads to distinct photoinduced dynamics. In particular, in ZnPc-C80, the energy of the charge transfer (CT) state from ZnPc to C80 is lower than that of the local excitation (LE) state of ZnPc, indicating that electrons tend to transfer from ZnPc to C80 following the LE of ZnPc. In contrast, in ZnPcS-C80, the lowest energy CT state corresponding to CT from C80 to ZnPcS is lower than that of the LE state of ZnPcS, suggesting that the excitation of ZnPcS preferentially induces hole transfer from ZnPcS to C80. Moreover, the inclusion of solvent effects is crucial for reordering the energies of the relevant states, highlighting the significant role of the solvent in the photoinduced dynamics. Nonadiabatic dynamics simulations further corroborate these findings: for ZnPc-C80, excitation at 633 nm results in energy transfer from ZnPc to C80 within the first 750 fs, followed by electron transfer, whereas for ZnPcS-C80, excitation at 663 nm leads to a concerted process of energy transfer and hole transfer from ZnPcS to C80. This work not only elucidates the mechanisms underlying experimental observations but also demonstrates that chemical modifications can modulate the roles of molecular fragments in organic donor–acceptor (D–A) structures, which could be helpful for the design of high-performance organic D–A structures in the future.
Sublinear scaling method for indirect spin–spin coupling constant calculations at Hartree–Fock and density functional theory level
The spin–spin coupling (SSC) phenomenon in nuclear magnetic resonance (NMR) spectroscopy is useful for determining the structures of unknown compounds. The SSC constants (SSCCs) can be obtained via quantum chemistry simulations. However, conventional analytical algorithms for simulating SSCCs are not applicable to large molecules due to their high computational costs. Building on recent advances in sublinear scaling (O(1)) methods, including the O(1) SSCC method developed by Luenser et al., J. Chem. Phys. 145, 124103 (2016), and the O(1) NMR shielding method by Yuan et al., J. Chem. Phys. 150, 154113 (2019), we have developed a sublinear scaling method to compute the SSCCs of molecules with hundreds of atoms. The accuracy of the O(1) method has been calibrated using the SSCCs of organic molecules, recovering ∼99.9% of the canonical one-bond SSCC results. In the present work, SSCCs in peptides, including those involving hydrogen bonds, have been computed and analyzed using the new O(1) method as well. The new O(1) method is able to address systems with more than ten thousand basis functions.
Simulating iron in oxygen-containing environments: An improved Fe–O interaction for density-functional tight-binding
The chemistry of iron in oxygen-containing and wet environments plays a central role in corrosion, (electro)catalytic reactions, and several biological processes. These processes hinge on the molecular-level interactions between iron and various oxygen-containing species such as water, molecular oxygen, oxygen radicals, and functional groups such as alcohols or carboxyls. Although the first-principles density-functional theory (DFT) describes these interactions well, DFT is often too slow to simulate the thermodynamics and kinetics of the above-mentioned processes at the necessary time and length scales. Fortunately, second-principles density-functional tight-binding (DFTB) satisfies these traits once properly parameterized for the target systems. Here, we discuss the problems that current DFTB parameterizations have with Fe–O pairwise repulsion, a central contributor to the DFTB performance. We construct an improved Fe–O repulsion by fitting the repulsion to structures relevant for topical research and benchmark it against structures with free and adsorbed Fe interacting with water and other oxygen-containing species. We explore the improved interaction by simulating the dynamics of atomic Fe and FeN4-modified graphene in aqueous environments, demonstrating the applicability of the parameterization to catalytically relevant large-scale simulations.
A five-terminal ITO transistor enabling memory, artificial synaptic behaviors, and logic operations
The increasing complexity of fabrication and high transistor density is slowing down progress in integrated circuits. Simplified designs are now critical to boost circuit performance while reducing manufacturing challenges. Meanwhile, ITO (Indium Tin Oxide)-based devices have recently gained attention due to their good mobility and large-scale availability. However, multifunctional ITO-based transistors combining memory, logic gates, and artificial synaptic behaviors are rarely reported. Here, we propose a multifunctional five-terminal ITO-based transistor. By introducing a multi-electrode design, the device shows potential in addressing the limitations of traditional one-dimensional/two-dimensional control modes, effectively integrating logic operations and memory functions while simulating brain-like behaviors of artificial synaptic electronic devices. Experimental results demonstrate that multi-electrode cooperative regulation significantly enhances the programmability and dynamic flexibility of the device. A single transistor can perform the logic gate switching of traditional logic gate circuits (logic AND/OR gates), greatly simplifying the circuit structure. This work not only provides new insights into the efficient and low-power design of neuromorphic computing and artificial intelligence hardware but also offers innovative references for the application of multi-dimensional regulation devices in complex brain-like function simulations.
Density-matrix embedding based multi-reference perturbation theory approach to single-ion magnets
Multi-configurational wave-function theory (MC-WFT) that combines the complete active space self-consistent field (CASSCF) approach with subsequent state interaction treatment of spin–orbit coupling, abbreviated as CASSCF-SO, plays important roles in the microscopic understanding of single-ion magnets (SIMs) with different central transition metal or lanthanide ions and various coordination environments, but its application to SIMs with complex structures is severely limited due to its highly demanding computational cost. Density-matrix embedding theory (DMET) provides a systematic and mathematically rigorous framework to combine low-level mean-field approaches like Hartree–Fock and high-level MC-WFT methods like CASSCF-SO, which is particularly promising for SIMs. As a continuation of our previous work on DMET + CASSCF for 3d SIMs [Ai et al., J. Phys. Chem. Lett. 13, 10627 (2022)], we extend the methodology by considering dynamic correlation on top of CASSCF using the second-order n-electron valence perturbation theory (NEVPT2) in the DMET framework, abbreviated as DMET + NEVPT2, and benchmark the accuracy of this approach to molecular magnetic anisotropy in a set of typical transition metal complexes. We found that DMET + NEVPT2 can give results very close to all-electron treatment, and can be systematically improved for higher accuracy by expanding the region treated as the central cluster, while the computational cost is dramatically reduced due to the reduction of the number of orbitals by DMET construction. Our findings suggest that the dynamic correlation treated at the NEVPT2 level, which is important for magnetic anisotropy in typical SIMs, can be well described in the DMET framework, which can facilitate high-accuracy ab initio spin–phonon relaxation study and high-throughput computations.
Hydrogen-bond rearrangements in the self-association and microhydration of ethylene glycol: A combined infrared and theoretical conformational sampling investigation
The hydrogen-bond rearrangements involved in the self-association and microhydration of the simplest vicinal diol, ethylene glycol (EG), have been explored by low-temperature mid- and far-IR cluster spectroscopy in doped neon “quantum” matrices at 4 K complemented by high-level quantum chemical conformational sampling. In addition to the reproduction of previous mid-IR jet assignments of the highly concerted hydrogen-bonded O–H stretching transitions, new distinct far-IR observations have been unambiguously attributed to transitions associated with concerted and highly anharmonic large-amplitude hindered OH (OD) torsional motion of (EG)2 and (EG-d2)2, respectively. These observations confirm the formation of a highly S4 symmetric global intermolecular potential energy minimum in the cryogenic neon environment associated with a very compact intermolecular hydrogen-bonded cyclic structure. In this conformation of (EG)2, the two intramolecular hydrogen bonds are rearranged into four new identical strongly cooperative intermolecular hydrogen bonds upon complexation as previously observed in supersonic jets. By means of selective complexation between EG and isotopically enriched H218O and D2O samples, the IR-active intramolecular hydrogen-bonded O–H stretching transitions furthermore are assigned unambiguously for the EG monohydrate. These spectroscopic observations reveal a cyclic cooperatively hydrogen-bonded structure, where the monomeric intramolecular hydrogen bond of EG is disrupted upon microhydration. In this detected conformation of the EG monohydrate, one hydroxy group acts as an intermolecular hydrogen bond donor to the H2O subunit and the vicinal hydroxy group as an intermolecular hydrogen bond acceptor to the H2O subunit in the cryogenic neon environment. The experimental findings are supported by quantum chemical analysis of the conformational potential energy landscape at the CCSD(T)-F12/cc-pVQZ-F12 level.
Scalable quantum simulations of molecular systems via improved optimization of neural quantum states
Quantum simulations of molecular systems hold transformative potential for computational chemistry, yet optimization inefficiencies and classical computational bottlenecks hinder practical implementation. We present algorithmic enhancements to the optimization of the unitary-coupled restricted Boltzmann machine Ansatz in the context of quantum machine learning, integrating adaptive learning rate and block optimization with the variational quantum imaginary time evolution algorithm. These improvements address convergence robustness and classical overhead in hybrid quantum–classical workflows. Demonstrations on small molecular systems show that our adaptive learning rate approach achieves chemically accurate results with fewer optimization steps compared to conventional methods, while block optimization further enables efficient parameter updates for larger systems, alleviating classical bottlenecks without compromising quantum expressivity. These advancements offer the possibility of extending the reach of near-term quantum hardware to scalable molecular simulations.
Universal structure of computing moments for exact quantum dynamics: Application to arbitrary system–bath couplings
We introduce a general procedure for computing higher-order moments of correlation functions in open quantum systems, extending the scope of our recent work on Memory Kernel Coupling Theory (MKCT) [Liu et al., arXiv:2407.01923 (2024)]. This approach is demonstrated for arbitrary system–bath coupling that can be expressed as a polynomial, HSB=V̂(α0+α1q̂+α2q̂2+⋯) , where we show that the recursive commutators of a system operator obey a universal hierarchy. Exploiting this structure, the higher-order moments are obtained by evaluating the expectation values of the system and bath operators separately, with bath expectation values derived from the derivatives of a generating function. We further apply MKCT to compute the dipole autocorrelation function for the spin-boson model with both linear and quadratic coupling, achieving agreement with the hierarchical equations of motion approach. Our findings suggest a promising path toward accurate dynamics for complex open quantum systems.