Penalty Reduction Research Articles

Blockchain-backed resilient strategies in a stochastic supply chain sourcing and distribution environment under disruption: implications for B2B sector

Purpose With the changing landscape of the globalised business world, business-to-business supply chains face a turbulent ocean of disruptions. Such is the effect that supply chains are disrupted to the point of failure, supply is halted and its adverse effect is seen on the consumer. While previous literature has extensively studied risk and resilience through mathematical modelling, this study aims to envision a novel supply chain model that integrates blockchain to support visibility and recovery resilience strategies. Design/methodology/approach The stochastic bi-objective (cost and shortage utility) optimisation-based mixed-integer linear programming model integrates blockchain through a binary variable, which activates at a particular threshold risk-averse level of the decision-maker. Findings Firstly, visibility is improved, as identified by the average reduction of penalties by 36% over the different scenarios. Secondly, the average sum of shortages over different scenarios is consequently reduced by 36% as the recovery of primary suppliers improves. Thirdly, the feeling of shortage unfairness between distributors is significantly reduced by applying blockchain. Fourthly, unreliable direct suppliers resume their supply due to the availability of timely information through blockchain. Lastly, reliance on backup suppliers is reduced as direct suppliers recover conveniently. Research limitations/implications The findings indicate that blockchain can enhance visibility and recovery even under high-impact disruption conditions. Furthermore, the study introduces a unique metric for measuring visibility, i.e. penalty costs (lower penalty costs indicate higher visibility and vice versa). The study also improves upon shortages and recoveries reported in prior literature by 6%. Finally, blockchain application caters to the literature on shortage unfairness by significantly reducing the feeling of shortage unfairness among distributors. Practical implications This study establishes blockchain as a pro-resilience technology. It advocates that organisations focus on investing in blockchain to enhance their visibility and recovery, as it effectively reduces absolute shortages and feelings of shortage unfairness while improving recovery and visibility. Originality/value To the best of the authors’ knowledge, this is a unique supply chain model study that integrates a technology such as blockchain directly as a binary variable in the model constraint equations while also focusing on resilience strategies, costs, risk aversion and shortage unfairness.

Improving Optical Transmission Performance in Multi-Channel Networks Utilizing Convolutional Neural Network-Enabled Digital Signal Processing to Mitigate Four-Wave Mixing

ABSTRACT The rapid growth of online services and the global transition to digital platforms, accelerated by the COVID-19 pandemic and the emergence of AI-based services, have led to a surge in demand for high-capacity optical communication networks (OCNs). However, this transition exacerbates the issue of fiber nonlinearity, notably four-wave mixing (FWM), which can significantly impact signal integrity in long-distance OCN transmissions with multiple channels. To address this challenge, this paper presents a novel approach leveraging a convolutional neural network (CNN)-based digital signal processing (DSP) model to mitigate the nonlinear effects of FWM on signal quality. The proposed CNN model, designed with three convolutional layers and trained on a comprehensive dataset of simulated OCN transmissions, demonstrates significant improvement in reducing nonlinear distortions caused by FWM. Our method is compared with traditional compensation techniques, such as digital back-propagation and Volterra series-based equalizers, showing a reduction in power penalties by 1 dB and an enhancement in the power budget by 2 dB. Simulation results indicate that the bit error rates (BERs) remain consistently below the critical threshold of 10−9 across various transmission distances, outperforming conventional methods. The simulation analysis, conducted on a 100 km multi-channel OCN testbed, confirms the CNN equalizer’s efficacy in reducing crosstalk and improving power efficiency, with a demonstrated 15% reduction in required launch power. Moreover, the analytical models used to evaluate the CNN-based DSP model show high accuracy in predicting performance, underscoring the model’s capability to achieve high-quality transmission with lower power requirements. These findings advocate for the integration of our CNN-based DSP model into OCNs, offering a fruitful solution for managing multi-channel, long-distance, and high-data-rate optical transmissions in real-world systems.

Achieving net zero energy penalty in post-combustion carbon capture through solar Energy: Parabolic trough and photovoltaic technologies

The adoption of carbon capture systems presents a pivotal strategy for mitigating greenhouse gas emissions, notably carbon dioxide. Nevertheless, the substantial surge in energy consumption associated with such systems remains a significant challenge. Addressing this challenge necessitates the integration of renewable energy sources. This study is dedicated to optimizing the conventional post-combustion carbon capture configuration, focusing on energy, exergy, and exergoeconomic considerations. The optimized configuration showcases a noteworthy 10 % reduction in overall energy penalties compared to its conventional counterpart, primarily attributed to diminished energy utilization in the reboiler. To achieve absolute sustainability and eliminate energy penalties in the optimized configuration, integration of a parabolic trough collector for steam provision to the reboiler and photovoltaic solar collectors for powering the plant’s equipment was undertaken. Furthermore, the incorporation of solar thermal storage tanks and batteries enables the storage of excess heat and electricity, ensuring operational continuity for up to 13 h in the absence of sunlight, such as during nighttime. The final optimized configuration manifests a commendable 14 % enhancement in exergoeconomic performance relative to the conventional configuration, thereby realizing zero energy penalties. This achievement renders the optimized configuration a compelling and viable choice for carbon capture units.

Facilitating proton-coupled electron transfer for energy-efficient CO2 desorption by C@ZrO2 hollow composites

Catalyst-aided CO2 desorption offers a promising reduction in the energy penalty of amine scrubbing, but faces the challenges of slow mass transfer, sluggish desorption kinetics, and susceptibility to deactivation. In this work, a hollow composite catalyst C@ZrO2 was developed to simultaneously realize rapid electron, proton and mass transfer for CO2 desorption via facilitating proton-coupled electron transfer (PCET) effect. The CO2 desorption rate of benchmark MEA solution increased by 126% and relative heat duty decreased by 69.9% in presence of C@ZrO2, and its catalytic performance didn’t noticeably decline after 10 cycles. Additionally, the desorption rate of biphasic solvents with a high viscosity increased by 112% and relative heat duty decreased by 57.3% with C@ZrO2. Based on theoretical calculation, the facilitated PCET efficiency of carbon layer increased the binding energy of carbamate to enhance its mass transfer rate from the liquid phase to the C@ZrO2 surface, and stretched the C-N bond to reduce the proton transfer energy barrier by 66.8%. This work provided a novel insight to design catalysts for energy-efficient and stable CO2 capture.

Profit-optimal data-driven operation of a hybrid power plant participating in energy markets

An energy management system (EMS) is formulated for a hybrid power plant (HPP), consisting of a wind power plant and battery storage plant, participating in bidding stages in the German energy market. The EMS utilizes supervisory control and data acquisition (SCADA) measurements from the site to improve power forecast from the wind power plant. First, the measurement data are used together with numerical weather prediction data to accurately forecast local wind conditions. Second, the measurement data are used to adapt a baseline engineering wake model that gives the total wind power generation for a given input wind condition. The EMS also uses an online cyclic damage minimization approach to accurately balance the battery damage cost against the revenue obtained by market bidding. An HPP controller is formulated to ensure proper tracking of optimal set-points. When compared with standard formulations, the proposed approach shows an accurate estimation and balancing of revenue and costs and a significant reduction in the power deviation penalty, which leads to significantly higher overall profit.

On the cost of zero carbon electricity: A techno-economic analysis of combined cycle gas turbines with post-combustion CO2 capture

To achieve a sustainable electricity grid, affordable and dispatchable power capacity that supports grid stability and does not increase atmospheric CO2 levels will be required. Combined cycle gas turbines (CCGTs) with post-combustion CO2 capture (PCC) can meet these requirements by capturing and permanently storing all combustion CO2 emissions and, coupled with negative emissions technologies, any remaining life-cycle emissions. For the first time, we present a comprehensive analysis of the technical and financial challenges of producing zero-carbon electricity from CCGTs on a life-cycle basis. We conclude that when the design is optimised, fossil CO2 capture fractions can be increased from 96% to 100% with minimal process modification, commercially available technology and an additional 0.5% decrease in thermal efficiency. This represents a significant 60–70% reduction in the additional efficiency penalty required to reach zero CO2 emission operation. The Cost of CO2 Avoided of 100% fossil CO2 capture is just 128 £/tCO2, a 3 £/tCO2 increase over the 95% gross CO2 capture fraction required to permit PCC projects in the UK. Indeed, within the bounds of the UK power CCS business model, we show that 100% fossil CO2 capture maximises both variable and capacity payments to the producer, resulting in a 2% decrease in the cost of power produced. For zero-carbon electricity on a life-cycle basis, the recapture and permanent geological storage of all remaining life-cycle CO2e emissions from plant construction & decommissioning, CO2 T&S network operation and the natural gas supply chain (operational CO2e emissions and methane leakage) increases the median Cost of CO2 Avoided to 178 £/tCO2 (130–371 £/tCO2), leading to the novel conclusion that a market mechanism equating to a CO2 price of over 178£/tCO2 is likely sufficient to incentivise the development of truly CO2-neutral CCGTs.

Performance of ChatGPT on the Taiwan urology board examination: insights into current strengths and shortcomings.

To compare ChatGPT-4 and ChatGPT-3.5's performance on Taiwan urology board examination (TUBE), focusing on answer accuracy, explanation consistency, and uncertainty management tactics to minimize score penalties from incorrect responses across 12 urology domains. 450 multiple-choice questions from TUBE(2020-2022) were presented to two models. Three urologists assessed correctness and consistency of each response. Accuracy quantifies correct answers; consistency assesses logic and coherence in explanations out of total responses, alongside a penalty reduction experiment with prompt variations. Univariate logistic regression was applied for subgroup comparison. ChatGPT-4 showed strengths in urology, achieved an overall accuracy of 57.8%, with annual accuracies of 64.7% (2020), 58.0% (2021), and 50.7% (2022), significantly surpassing ChatGPT-3.5 (33.8%, OR = 2.68, 95% CI [2.05-3.52]). It could have passed the TUBE written exams if solely based on accuracy but failed in the final score due to penalties. ChatGPT-4 displayed a declining accuracy trend over time. Variability in accuracy across 12 urological domains was noted, with more frequently updated knowledge domains showing lower accuracy (53.2% vs. 62.2%, OR = 0.69, p = 0.05). A high consistency rate of 91.6% in explanations across all domains indicates reliable delivery of coherent and logical information. The simple prompt outperformed strategy-based prompts in accuracy (60% vs. 40%, p = 0.016), highlighting ChatGPT's limitations in its inability to accurately self-assess uncertainty and a tendency towards overconfidence, which may hinder medical decision-making. ChatGPT-4's high accuracy and consistent explanations in urology board examination demonstrate its potential in medical information processing. However, its limitations in self-assessment and overconfidence necessitate caution in its application, especially for inexperienced users. These insights call for ongoing advancements of urology-specific AI tools.

Proposal and thermodynamic investigation of pressurized calcium looping integrated with chemical looping combustion for tail-end CO2 capture in a retrofitted natural gas combined cycle power plant

The integration of tail-end calcium looping into an existing natural gas combined cycle (NGCC) power plant has minimal impact on CO2 capture retrofits. However, a high volume of flue gas needs to be preheated before entering the carbonator, and the relatively high energy consumption of oxygen production exacerbates the energy penalty of the NGCC system with tail-end CO2 capture. This paper proposes the method of pressurized calcium looping integrated with chemical looping combustion (PCaL-CLC). It employs the PCaL-CLC method to reduce the energy penalty and energy consumption of the NGCC system with tail-end CO2 capture. Results show that the proposed system using the PCaL-CLC method achieves a 3.0% reduction in energy penalty, decreasing from 9.1% in the reference system employing the calcium looping method to 6.1% in the proposed system. Besides, the specific energy consumption for CO2 avoided (SPECCA) declines from 4.43 MJLHV/kg CO2 to 2.76 MJLHV/kg CO2. Exergy analysis and energy utilization diagrams reveal the underlying reason for improving system performance. Furthermore, by optimizing the operating parameters of the gas turbine and equipping it with advanced heat recovery steam generation, an energy penalty of 2.9% and a SPECCA of 1.21 MJLHV/kg CO2 are achieved without CO2 compression, which is superior to those of amine scrubbing and hot-end calcium looping CO2 capture technologies. The proposed PCaL-CLC method offers an alternative approach to reducing the energy consumption of tail-end CO2 capture in existing natural gas combined cycle power plants.

Exploring electric vehicle's potential as capacity reservation through V2G operation to compensate load deviation in distribution systems

This paper addresses the significant challenges faced by distribution system operators (DSOs) in competitive electricity markets due to uncertainties arising from electricity markets, electric vehicles (EVs), and conventional loads. To tackle these challenges, this paper proposes a pseudo-local reserve market between the DSO and EVs, which enables the DSO to integrate EV flexibility into the overall market framework while compensating for deviations in the conventional load across the wholesale electricity market. Furthermore, a two-stage framework is developed to facilitate the participation of EVs in electricity markets. In the first stage, the reserve capacity of EVs is integrated into the decision-making process for day-ahead bidding, taking into account uncertainties of the load and electricity. In the second stage, the day-ahead results are coordinated to enable the efficient dispatch of EVs for real-time market participation. To assess the efficacy of the proposed framework, a case study is conducted within a 31-node distribution system situated on a university campus located in Guangdong, China. This paper investigates the economic impact of load deviation constraints on EV reserves, revealing a penalty reduction of 3100 CNY for a daily reservation of 1000 EVs and a net profit increase of 1300 CNY for DSOs utilizing reserves. It further introduces a method for quantifying reserve capacity, enhancing DSO decision-making accuracy.

Technical and economic performance assessment of blue hydrogen production using new configuration through modelling and simulation

Steam methane reforming (SMR) is the dominant process for hydrogen production, which produce large amount of carbon dioxide (CO2) as a by-product. To address concerns about carbon emissions, there is an increasing focus on blue hydrogen to mitigate carbon emissions during hydrogen production. However, the commercialization of blue hydrogen production (BHP) is hindered by the challenges of high cost and energy consumption. This study proposes a new configuration to address these challenges, which is characterized by: (a) the use of piperazine (PZ) as a solvent, which has a high CO2 absorption efficiency; (b) a more efficient heat exchange configuration which recovers the waste exergy from flue gas; (c) the advanced flash stripper (AFS) was adopted to reduce the capital cost due to its simpler stripper configuration. In addition, the technical and economic performance of the proposed energy and cost-saving blue hydrogen production (ECSB) process is investigated and compared with the standard SMR process. The detailed models of the SMR process and the post-combustion carbon capture (PCC) process were developed and integrated in Aspen plus® V11. The results of the technical analysis showed that the ECSB process with 30 wt.% PZ achieves a 36.3 % reduction in energy penalty when compared to the standard process with 30 wt.% Monoethanolamine (MEA). The results of the economic analysis showed that the lowest levelized cost of blue hydrogen (LCBH) was achieved by the ECSB process with 30 wt.% PZ. Compared to the BHP process with 30 wt.% MEA, the LCBH was reduced by 19.7 %.

Unveiling the Motivations Behind Malaysian Taxpayer Participation in Voluntary Disclosure Programme

In the pursuit of enhanced tax compliance, voluntary disclosure programmes (VDP) serve as valuable tools when executed effectively. This study delves into tax professionals’ perspectives on factors influencing taxpayer participation in Malaysia’s VDP when first introduced in 2015 to boost revenue and compliance. This survey of 135 tax practitioners from prominent firms in Johor Bahru and Kuala Lumpur sheds light on critical VDP participation drivers. The findings indicate that the VDP’s success hinges on several factors. Foremost among these is the size of penalty reduction, which holds the greatest sway in motivating participation. Following closely is the apprehension of further audits, while fear of detection and punishment ranks third. The efforts made by the Inland Revenue Board of Malaysia in promoting the VDP emerge as the fourth significant driver. This study, among the first to explore VDP implementation in Malaysia, anticipates inspiring future research and policy refinements in the realm of tax compliance.

Assessment of minimum allowable thickness of advanced steel (FeCrAl) cladding for accident tolerant fuel

The ferritic iron-chromium-aluminum (FeCrAl) alloy cladding is considered to be the most promising for near-term application in the ATF framework to replace existing zirconium alloy cladding. Although FeCrAl cladding presents several advantages, it is well known that there are at least two main drawbacks, one is the increased thermal neutron absorption cross-section compared to the current Zr-based cladding resulting in a neutronic penalty and another is tritium higher permeation. In the present study, the minimum allowable thickness of cladding is addressed considering neutronic penalty reduction and the mechanical-structural behavior under the LOCA accident condition. The neutronic penalty assessment was performed using the Monte Carlo code and mechanical-structural performance of the FeCrAl cladding using the TRANSURANUS fuel code, which was modified to consider properly the FeCrAl cladding.

Microsecond dynamics of H10N7 influenza neuraminidase reveals the plasticity of loop regions and drug resistance due to the R292K mutation.

At the beginning of the last century, multiple pandemics caused by influenza (flu) viruses severely impacted public health. Despite the development of vaccinations and antiviral medications to prevent and control impending flu outbreaks, unforeseen novel strains and continuously evolving old strains continue to represent a serious threat to human life. Therefore, the recently identified H10N7, for which not much data is available for rational structure-based drug design, needs to be further explored. Here, we investigated the structural dynamics of neuraminidase N7 upon binding of inhibitors, and the drug resistance mechanisms against the oseltamivir (OTV) and laninamivir (LNV) antivirals due to the crucial R292K mutation on the N7 using the computational microscope, molecular dynamics (MD) simulations. In this study, each system underwent long 2 × 1 μs MD simulations to answer the conformational changes and drug resistance mechanisms. These long time-scale dynamics simulations and free energy landscapes demonstrated that the mutant systems showed a high degree of conformational variation compared to their wildtype (WT) counterparts, and the LNV-bound mutant exhibited an extended 150-loop conformation. Further, the molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) calculation and MM/GBSA free energy decomposition were used to characterize the binding of OTV and LNV with WT, and R292K mutated N7, revealing the R292K mutation as drug-resistant, facilitated by a decline in binding interaction and a reduction in the dehydration penalty. Due to the broader binding pocket cavity of the smaller K292 mutant residue relative to the wildtype, the drug carboxylate to K292 hydrogen bonding was lost, and the area surrounding the K292 residue was more accessible to water molecules. This implies that drug resistance could be reduced by strengthening the hydrogen bond contacts between N7 inhibitors and altered N7, creating inhibitors that can form a hydrogen bond to the mutant K292, or preserving the closed cavity conformations.

Diminished criminal responsibility: A multinational comparative review

This article reviews the legal frameworks of diminished criminal responsibility in eighteen civil law jurisdictions across the globe—Brazil, Chile, China, the Czech Republic, Finland, France, Germany, Greece, Italy, Japan, Luxembourg, Poland, Portugal, Russia, Spain, Switzerland, Taiwan, and Turkey. Specifically, it reports the legal standards and main features of partial responsibility, associated penalty reductions, and potential dispositions following a partial responsibility finding. It also surveys empirical data on the prevalence of diminished responsibility as compared to criminal nonresponsibility. This article, which reflects contemporary penal codes and draws from both English and non-English sources, is the only known existing source to compile these partial responsibility standards or to delineate their precise sentencing consequences. It is also the only known source in English to describe Portugal's and Chile's treatment of diminished responsibility. Providing a comparative overview of graduated responsibility in nearly twenty countries invites global discussion on whether and how society should recognize partial responsibility, as well as the punitive and therapeutic consequences that should attend this finding.

Humanitarian transportation network design via two-stage distributionally robust optimization

Natural disasters are highly unpredictable, with varying degrees of magnitude, and thus require a reliable and robust humanitarian relief network. Faced with the adverse effects of disasters, we advocate taking pre-disaster preventive actions, e.g., road link strengthening, to mitigate post-disaster disruptions to road networks. In this paper, we study a highly integrated humanitarian relief network design problem, in which the network strengthening plan and inventory pre-positioning scheme are optimized cooperatively. The proposed problem is formulated as a two-stage distributionally robust optimization (DRO) model, in which the first and second stages correspond to pre- and post-disaster relief operations, respectively. By leveraging prior data and the Wasserstein metric, a tailored ambiguity set is constructed to capture both node- and link-wise uncertainties. We demonstrate that the two-stage DRO model over the Wasserstein ambiguity set has an equivalent reformulation that can be solved via the L-shaped method with bilinear subproblems. Based on observations of the problem structure and the spirit of separation optimization, both exact and heuristic approaches are proposed to address the bilinear subproblems. Via the case study of the Yushu earthquake, we highlight the value of jointly optimizing network strengthening and inventory pre-positioning decisions. Specifically, with the same investment budget, integrating network strengthening into inventory pre-positioning can easily achieve an approximately 60% reduction in shortage penalties. Furthermore, our method can produce reliable solutions, based on which we explore several managerial implications.

Fractional fuzzy PI controller using particle swarm optimization to improve power factor by boost converter

The power circuit of AC voltage controller capable of operating at a leading, lagging, and unity power factor is studied by a lot of researchers in the literature. Circuits working with high switching frequency are known as power factor correctors (PFCs). The single-phase boost converter has become the most popular topology for power factor correction (PFC) in general purpose power supplies. Power factor correction circuit provides conventional benefits to electric power systems. The benefits are the reduction of power factor penalty and utility bill and power loss. Therefore, a boost converter power factor correction scheme is presented in this paper. A PI, fuzzy logic PI and fractional order PI (FOPI) controllers are used to fix an active shaping of input current of the circuit and to improve the power factor. The controller parameters (coefficients) are optimized using the Particle Swarm Optimization (PSO) algorithm. Average current mode control (ACMC) method is used in the circuit. The converter circuit consists of a single-phase bridge rectifier, boost converter, transformer and load. A mathematical model of the plant is required to design the PI controller. A model for power factor correction circuit is formed in MATLAB/Simulink toolbox and a filter is designed to reduce THD value. The proposed model is simulated using a combination of PI, fuzzy logic and FOPI controllers. The control scheme is applied to 600 Watt PFC boost converter to get 400 Volt DC output voltage and 0.99 power factor. The input voltage is 230 VRMS with 50 Hz. The combination of FOPI and PI controller has the best solution to control the power factor according to PI and fuzzy controllers.

Molecular Crowders Can Induce Collapse in Hydrophilic Polymers via Soft Attractive Interactions.

A comprehensive understanding of protein folding and biomolecular self-assembly in the intracellular environment requires obtaining a microscopic view of the crowding effects. The classical view of crowding explains biomolecular collapse in such an environment in terms of the entropic solvent excluded volume effects subjected to hard-core repulsions exerted by the inert crowders, neglecting their soft chemical interactions. In this study, the effects of nonspecific, soft interactions of molecular crowders in regulating the conformational equilibrium of hydrophilic (charged) polymers are examined. Using advanced molecular dynamics simulations, collapse free energies of an uncharged, a negatively charged, and a charge-neutral 32-mer generic polymer are computed. The strength of the polymer-crowder dispersion energy is modulated to examine its effect on polymer collapse. The results show that the crowders preferentially adsorb and drive the collapse of all three polymers. The uncharged polymer collapse is opposed by the change in solute-solvent interaction energy but is overcompensated by the favorable change in the solute-solvent entropy as observed in hydrophobic collapse. However, the negatively charged polymer collapses with a favorable change in solute-solvent interaction energy due to reduction in the dehydration energy penalty as the crowders partition to the polymer interface and shield the charged beads. The collapse of a charge-neutral polymer is opposed by the solute-solvent interaction energy but is overcompensated by the solute-solvent entropy change. However, for the strongly interacting crowders, the overall energetic penalty decreases since the crowders interact with polymer beads via cohesive bridging attractions to induce polymer collapse. These bridging attractions are found to be sensitive to the binding sites of the polymer, since they are absent in the negatively charged or uncharged polymers. These interesting differences in thermodynamic driving forces highlight the crucial role of the chemical nature of the macromolecule as well as of the crowder in determining the conformational equilibria in a crowded milieu. The results emphasize that the chemical interactions of the crowders should be explicitly considered to account for the crowding effects. The findings have implications in understanding the crowding effects on the protein free energy landscapes.

Reduction of Contractual Penalty in Conformity with Polish Law Against the background of Supranational Legal Regulations

W artykule przedstawiona została problematyka miarkowania kary umownej według prawa polskiego na tle ponadnarodowych uregulowań prawnych. Celem artykułu jest ustalenie, czy obecne unormowanie w prawie polskim miarkowania kary umownej (art. 484 § 2 Kodeksu Cywilnego) jest dostoswane do standardów, które można wywieść z ponadnarodowych regulacji prawnych, tj. Rezolucji (78) 3 Rady Europy o karach umownych w prawie cywilnym, Zasad Międzynarodowych Kontraktów Handlowych UNIDROIT, Zasad Europejskiego Prawa Umów PECL, Projektu Wspólnej Ramy Odniesienia DCFR i Zasada TransLex, a także sformułowanie wniosków de lege ferenda. W artykule używana jest metoda logiczno-językowa i prawnoporównawcza. Na początku przedstawiona została regulacja prawna miarkowania kary umownej w prawie polskim. Następnie, przedstawione zostało miarkowanie kary umownej w ponadnarodowych regulacja soft law wymienionych powyżej. W końcu została sformułowane wnioski płynące z przeprowadzonej analizy. Pomimo pewnych mankamentów, regulacja miarkowania kary umownej w prawie polskim wydaje się odpowiadać rozwiązaniom zawartym w wyżej wskazanych regulacjach o charakterze ponadnarodowym. Pewnych zmian wymaga katalog przesłanek miarkowania kary umownej i ograniczenie dowolności co do zakresu redukcji kary umownej.

Differentiation of criminal liability in unfinished criminal offenses

The article deals with issues related to the differentiation of criminal responsibility in case of preparation or attempt to commit a criminal act. The author expressed arguments that social danger is always evident by the preparation of towers on the one hand and by an attempt and completed crime on the other. However, establishing a clear difference between the public danger of an attempt and a completed criminal offense is premature and requires assessment at the stage of individualization of criminal responsibility. There are not always reasons for ascertaining a clear decrease in the level of public danger committed at the stage of an attempt. That is why the imperative approach to the differentiation of criminal responsibility between an attempt and a finished criminal offense by means of a mandatory reduction of the maximum penalty is cause for concern. It is more justified to solve this issue not categorically, that is, not by differentiating criminal responsibility, but by individualizing the latter. It is proposed that criminal liability for preparation should be imposed only for the range of criminal offenses clearly defined in a separate article of the General Part of the Criminal Code, based on taking into account the object of the offense and the nature of the socially dangerous act. It is not enough to base only on the categorization of criminal offenses to determine the range of those compounds, the preparation of which should attract criminal liability. As a result, the lack of grounds for imperative differentiation of criminal responsibility between an attempt and a completed crime is substantiated, in particular, it is worth abandoning the legislative approach to reducing the upper limit of the most severe punishment in the case of an attempt. At the same time, lowering the upper limit of the most severe punishment in the case of preparation for a criminal offense is correct. Key words: differentiation, criminal liability, preparation, attempt, stage.

Effect of Cas9 Protein on the Seed-Target Base Pair of the sgRNA/DNA Hybrid Duplex.

CRISPR (clustered regularly interspaced short palindromic repeats)/CRISPR-associated protein (Cas9) has been widely used for gene editing. Not all guide RNAs can cleave the DNA efficiently remains a major challenge to CRISPR/Cas9-mediated genome engineering. Therefore, understanding how the Cas9 complex successfully and efficiently identifies specific functional targets through base-pairing has great implications for such applications. The 10-nt seed sequence at the 3' end of the guide RNA is critical to target recognition and cleavage. Here, through stretching molecular dynamics simulation, we studied the thermodynamics and kinetics of the binding-dissociation process of the seed base and the target DNA base with the Cas9 protein. The results showed that in the presence of Cas9 protein, the enthalpy change and entropy change in binding-dissociation of the seed base with the target are smaller than those without the Cas9 protein. The reduction of entropy penalty upon association with the protein resulted from the pre-organization of the seed base in an A-form helix, and the reduction of enthalpy change was due to the electrostatic attraction of the positively charged channel with the negative target DNA. The binding barrier coming from the entropy loss and the dissociation barrier resulting from the destruction of the base pair in the presence of Cas9 protein were lower than those without protein, which indicates that the seed region is crucial for efficiently searching the correct target by accelerating the binding rate and dissociating fast from the wrong target.