Specific Problems Research Articles

The problem with criminal records: Discrepancies between state reports and private‐sector background checks

AbstractCriminal records are routinely used by employers and other institutional decision‐makers who rely on their presumed fidelity to evaluate applicants. We analyze criminal records for a sample of 101 people, comparing official state reports, two sources of private‐sector background checks (one regulated and one unregulated by federal law), and qualitative interviews. Based on our analysis, private‐sector background checks are laden with false‐positive and false‐negative errors: 60 percent and 50 percent of participants had at least one false‐positive error on their regulated and unregulated background checks, and nearly all (90 percent and 92 percent of participants, respectively) had at least one false‐negative error. We define specific problems with private‐sector criminal records: mismatched data that create false negatives, missing case dispositions that create incomplete and misleading criminal records, and incorrect data that create false positives. Accompanying qualitative interviews show how errors in background checks limit access to social opportunities ranging from employment to education to housing and violate basic principles of fairness in the legal system.

Instagram as A Digital Media to Build Self-Acceptance

One of the effects of Broken Home children is the difficulty in accepting their condition, which causes their Self-Acceptance. Children who find it challenging to build Self-Acceptance will affect their self-concept, so they continue to think negatively. This research focuses on analyzing the content of digital media Instagram that is present as a communication tool to provide educational information for generation Z related to specific problems, especially about Self-Acceptance. The presence of social media in the digital era can now be used as a means of long-distance communication and help educate its users. The social media that is popular among Generation Z is Instagram. The object of this research is the Instagram account @Behome.id. The data is obtained from content from the @Behome.id account, which has information about Self-Acceptance. This research uses a qualitative content analysis method with the theory of self-acceptance and new media. This research concludes that Behome.id provides tips such as a friend who embraces another friend by using a casual style of language, mapping broken home children tend to have low self-acceptance due to lack of self-disclosure to others, giving many tips to broken home children to be more can get their emotions out in order to express themselves.

A Performance Evaluation Method for Employees in Small and Medium-Sized IT Enterprises Based on Multiple Indicators

In recent years, research on performance evaluation of IT enterprises has become a hot topic worthy of attention. In some countries, IT enterprises have become essential in driving economic development. However, there are significant differences in personnel management, performance evaluation, and other aspects among listed IT enterprises, large IT enterprises, and small and medium-sized IT enterprises, making it difficult to standardize performance evaluation for different types of enterprises. Especially for small and medium-sized IT enterprises, there are still specific problems in performance evaluation due to the unique characteristics of the enterprise. The primary manifestation is that standardized evaluation indicators cannot be fully applicable to small and medium-sized IT enterprises, making it challenging to conduct dynamic evaluations based on the characteristics of the enterprise. This article is based on the research and analysis data of performance evaluation management for small and medium-sized IT enterprises in a particular region of China. It proposes a multi-indicator-oriented performance evaluation system for small and medium-sized IT enterprises and offers corresponding guarantee measures.

Pengaruh Kepercayaan Konsumen Terhadap Developer Dalam Pelaksanaan Perjanjian Pengadaan Perumahan

The main problem examined in this context is how the developer fulfills its obligations to consumers who have made payments. The method used is banking mediation, aiming to provide a comprehensive, complete, and systematic overview of the implementation. This research is descriptive, where conclusions are drawn from general issues faced by consumers regarding specific problems. Furthermore, legal materials are analyzed to see if they can provide a solution or an overall picture of the issue. Thus, this study attempts to provide a comprehensive understanding of conflict resolution between developers and consumers in the context of housing development in Indonesia

General and Specific Cytotoxicity of Chimeric Antisense Oligonucleotides in Bacterial Cells and Human Cell Lines.

In the last two decades, antisense oligonucleotide technology has emerged as a promising approach to tackling various healthcare issues and diseases, such as antimicrobial resistance, cancer, and neurodegenerative diseases. Despite the numerous improvements in the structure and modifications of the antisense oligonucleotides (ASOs), there are still specific problems with their clinical efficacy and preclinical cytotoxicity results. To better understand the effects of the ASOs in this paper, we conducted many MTT assays to assess the general and specific cytotoxicity of four new chimeric ASOs in bacterial cells and human cell lines. We demonstrate the absence of inhibitory activity in the human pathogenic bacteria Staphylococcus aureus by non-specific ASOs. The pVEC-ASO1 and pVEC-ASO2 are designed to have no specific targets in S. aureus. They have only partial hybridization to the guanylate kinase mRNA. The pVEC-ASO3 targets UBA2 mRNA, a hallmark cancer pathology in MYC-driven cancer, while pVEC-ASO4 has no complementary sequences. We discovered some cytotoxicity of the non-specific ASOs in healthy and cancer human cell lines. The results are compared with two other ASOs, targeting specific mRNA in cancer cells. All ASOs are delivered into the cell via the cell-penetrating oligopeptide pVEC, which is attached to them. We draw a good correlation between the thermodynamic stability of ASO/target RNA and the toxicity effect in human cell lines. The data obtained signify the importance of thorough bioinformatic analysis and high specificity in designing and developing novel ASOs for safer therapeutic agents in clinical practice.

Synthesis of Optimal Control of Spacecraft Angular Momentum for Spatial Turn Taking into Account Energy Costs Using Quaternions

Background: In this paper, we propose solving the specific original problem of control synthesis of spacecraft attitude. Optimization of the control program is made with the use of a new criterion of quality that combines energy costs and duration of reorientation under restrictions on control (the presence of a time factor limits the duration of slew maneuver). Methods: The construction of optimal control for angular momentum change is based on the quaternion method and L.S. Pontryagin maximum principle. An analytical solution to the problem was obtained on the base of a differential equation relating the orientation quaternion and angular momentum of a spacecraft. Results: Key properties of the optimal solution are formulated in analytical form; the features of optimal motion are studied in detail. The control law is formulated in the form of explicit dependence between control and phase variables. In a case when the controlling torque is limited by the given restriction (at the beginning and end of a turn), analytical formulas have been written for the duration of braking and acceleration. Main relations which determine optimal values of parameters of the algorithm for control of angular momentum are given. Examples and results of mathematical modeling of spacecraft motion formed by optimal control were given. This data in addition to the theoretical descriptions illustrates the process of reorientation in evident form and demonstrates the practical feasibility of a designed method for control of angular momentum during spatial turn. Conclusion: The designed optimal algorithm of control of spacecraft motion improves the efficiency of spacecraft attitude system, and originates more economical performance of spacecraft during flight on orbit.

Validation of PleaseApp: a digital tool for the assessment of receptive pragmatic abilities in children with neurodevelopmental disorders.

Pragmatic skills allow children to use language for social purposes, that is, to communicate and interact with people. Most children with neurodevelopmental disorders (NDDs) face pragmatic difficulties during development. Nevertheless, pragmatic skills are often only partially assessed because the existing instruments usually focus on specific aspects of pragmatics and are not always adapted to children with communication difficulties. In this sense, digital tools (e.g., apps) are an optimal method to compensate for some difficulties. Moreover, there is a lack of pragmatic tools measuring the receptive domain. Therefore, the present study aims to validate PleaseApp as a digital instrument that measures eight pragmatic skills by presenting the design of the assessment tool and its psychometric properties. PleaseApp was designed based on previous empirical studies of developmental pragmatics in children with and without NDD. PleaseApp assesses eight receptive pragmatic skills: figurative language, narrative, reference, indirect speech acts, visual and verbal humor, gesture-speech integration, politeness, and complex intentionality. The study involved 150 typically developing children between 5 and 12 years of age. A confirmatory factor analysis proposes an eight-factor model with no underlying factor structure. The eight tests that compose PleaseApp have obtained a model with a good fit and with adequate reliability and validity indices. PleaseApp is an objective, valid, and reliable tool for assessing pragmatic skills in children with NDD. In this sense, it helps to assess whether a child has acquired pragmatic skills correctly according to his/her age and clarify the specific problems a child has in eight different components to plan personal and personalized interventions.

Research On Pruning Methods for Mobilenet Convolutional Neural Network

This paper comprehensively reviews pruning methods for MobileNet convolutional neural networks. MobileNet is a lightweight convolutional neural network suitable for resource-constrained environments such as mobile devices.Various pruning methods can be applied to reduce the model's storage space and computational complexity, including channel pruning, kernel pruning, and weight pruning. Channel pruning removes unimportant channels to reduce redundant parameters and computations in the model, while kernel pruning reduces redundant calculations by pruning convolutional kernels. Weight pruning involves setting small-weighted elements to zero to remove unimportant weights. These pruning methods can be used individually or in combination. After pruning, fine-tuning is necessary to restore the model's performance. Factors such as pruning rate, pruning order, and pruning location need to be considered to achieve a balance between reducing model size and computational complexity while minimizing performance loss. Pruning methods based on MobileNet convolutional neural networks reduce the parameter count and computational complexity, improving model lightweightness and inference efficiency. These methods are of significant value in resource-constrained environments such as mobile devices. This review provides insights into pruning methods for MobileNet convolutional neural networks and their applications in lightweight and efficient model deployment. Further advancements such as automated pruning methods driven by reinforcement learning algorithms can enhance the pruning process to achieve optimal model compression effects. Future research should focus on adapting and optimizing these pruning methods for specific problem domains and achieving even higher compression ratios and computational speedups.

Letter as Subject for Anthropological Research

The article discusses the value and possible results of the anthropological research focusing on ordinary letters. An ordinary letter is considered in the article to be written primarily for maintaining a relationship with the addressee, rather than for solving specific problems in a certain field (even if that includes research, culture, art, business, or legal issues). The anthropological research of ordinary letters is valuable in that it reveals the less visible patterns of communication and cooperation. This analysis primarily displays the temporality of communication and togetherness, showing correspondence as a rhythmic bidirectional continuous process of different intensity; secondly, it highlights the composition of the momentary “I”, which depends on the relationship with the addressee and draws together episodes from different spaces and times; and finally, it discloses the constant negotiations with the proposed or imposed roles – these negotiations are most clearly visible in the ordinary letters and, at the same time, they clearly vary depending on the relationship maintained by the particular thread of correspondence.
 The article also uses theoretical insights by scholars researching the epistolary materials (Liz Stanley, Helen Dampier, Aistė Kučinskienė) and those by anthropologists and philosophers (William James, Maurice Blanchot, Judith Butler, Jens Brockmeier, Harold Garfinkel, Hanna Meretoja), including the classical theories of time, yet again reminding us of the heterogeneity of the time experience and human actions. The correspondence of the Lithuanian poet Janina Degutytė was chosen as a suitable example, since it most clearly reveals various aspects of the ordinary letters discussed in the article.

A Performance Evaluation of Repetitive and Iterative Learning Algorithms for Periodic Tracking Control of Functional Electrical Stimulation System

Functional electrical stimulation (FES) is a medical device that delivers electrical pulses to the muscle, allowing patients with spinal cord injuries to perform activities such as walking, cycling, and grasping. It is critical for the FES to generate stimuli with the appropriate controller so that the desired movements can be precisely tracked. By considering the repetitive nature of the movements, the learning-based control algorithms are utilized for regulating the FES. Iterative learning control (ILC) and repetitive control (RC) are two learning algorithms that can be used to accomplish accurate repetitive motions. This study investigates a variety of ILC and RC designs with distinct learning functions; this constitutes our contribution to the field. The FES model of ankle angle, which is in a class of discrete-time linear systems is considered in this study. Two learning functions, i.e., proportional, and zero-phase learning functions, are simulated for the second-order FES model running at a sampling time of 0.1 s. The results indicate the superior performance of the ILC and RC in terms of convergence rate using the zero-phase learning function. ILC and RC with a zero-phase learning function can reach a zero root-mean-square error in two iterations if the model of the plant is correct. This is faster than proportional-based ILC and RC, which takes about 40 iterations. This indicates that the zero-phase learning function requires two iterations to ensure that the patient's ankle angle precisely tracks the intended trajectory. However, the tracking performance is degraded for both control methods, especially when the model is subject to uncertainties. This specific problem can lead to future research directions.

Why Parents Do Not Use Digital Health Interventions for Their Child's Mental Health?

There are free, evidence-based Digital Health Interventions (DHIs) that can help children's mental health, but few parents use them. We sought to understand what influenced uptake of DHIs by parents of children aged 2-12 years old with a mental health problem. We interviewed parents and analysed data using inductive content analysis. Four factors emerged: i) personal capacity; ii) awareness of DHIs and where to find one; iii) credibility, including trust and endorsement from experts; and iv) the suitability of a DHI to their child's specific problem and level of need. Incorporating these themes into the design of future DHIs may improve uptake.

Sleep Health among Children Adopted from Foster Care: The Moderating Effect of Parent–Child Sleep Interactions

ABSTRACT Objectives Sleep disruption is prevalent among children placed in foster care, elevating risk for a range of deleterious outcomes. Theoretically, achieving permanency via adoption may have a positive influence on children’s sleep via the presence of various factors, but little is known about the sleep health of children adopted from foster care, including predictors and moderators of sleep health. Method The current study included 226 parents who adopted a child from foster care in the U.S. (aged 4–11 years) within the past two years and a propensity score matched sample of 379 caregivers of children currently in foster care. Both samples completed online questionnaires about their child’s sleep, physical, and mental health. Results Comparatively, children in foster care experienced more nightmares, night terrors, moving to someone else’s’ bed during the night, and worse overall sleep quality, whereas adopted children were reported to experience significantly more nighttime awakenings. In the adopted sample, a greater number of prior foster placements unexpectedly predicted lower total sleep disturbance scores, but this relationship was moderated by parent–child interactions around sleep. In general, greater parental involvement in children’s sleep was associated with lower levels of child sleep disturbance. Conclusions Findings suggest that while specific sleep problems might remit after children in foster care achieve permanence, nighttime sleep fragmentation often persists. Parent–child interactions surrounding sleep may be pivotal in improving sleep health in this population.

Essential Principles of Postharvest Heat Treatments in Fruit Crops

In recent years, the field of heat treatment for commodities, particularly in the context of pest control and pathogen reduction, has advanced significantly. Hot water treatments (HWT) have emerged as a promising solution, addressing a range of postharvest challenges, from insect control to preventing fungal development and storage disorders like chilling injury. These treatments involve diverse time and temperature conditions, spanning from extended exposure at temperatures around 35 - 39°C in hot air to brief bursts at temperatures up to 63°C in hot water. Historically, much of the research in this field has been focused on solving specific problems, with less attention given to understanding how commodities themselves respond to these treatments. However, since the beginning of the 21st century, several research groups have taken an active interest in exploring the molecular responses and changes that occur within commodities subjected to heat treatment. By investigating these responses, researchers aim to not only optimize heat treatment strategies but also gain a deeper understanding of how commodities interact with these processes. In essence, this review provides valuable insights into the molecular dynamics of commodities undergoing heat treatments, shedding light on the intricate biochemical processes that influence their postharvest quality and safety.

Hybrid Quantum Technologies for Quantum Support Vector Machines

Quantum computing has rapidly gained prominence for its unprecedented computational efficiency in solving specific problems when compared to classical computing counterparts. This surge in attention is particularly pronounced in the realm of quantum machine learning (QML) following a classical trend. Here we start with a comprehensive overview of the current state-of-the-art in Quantum Support Vector Machines (QSVMs). Subsequently, we analyze the limitations inherent in both annealing and gate-based techniques. To address these identified weaknesses, we propose a novel hybrid methodology that integrates aspects of both techniques, thereby mitigating several individual drawbacks while keeping the advantages. We provide a detailed presentation of the two components of our hybrid models, accompanied by the presentation of experimental results that corroborate the efficacy of the proposed architecture. These results pave the way for a more integrated paradigm in quantum machine learning and quantum computing at large, transcending traditional compartmentalization.

Evaluating mechanical, thermal, and water absorption properties of biocomposites with Opuntia cladode fiber and palm flower biochar for industrial applications

This study addresses the development of environmentally friendly biocomposites using Opuntia cladode fiber and palm flower biochar for industrial applications. Derived sustainably, these materials significantly enhance mechanical properties, exemplified by Composite C3 (Resin 57wt.%, Fiber 40 wt%, Biochar 3 wt%) with notable flexural strength (217 MPa), tensile strength (178 MPa), impact strength (7.2 J), and hardness (92 Shore-D). However, a 5% biochar concentration led to a slight property decline. Thermal conductivity increased proportionally with biochar concentration, ranging from 0.36 to 0.49 W/mK, with biochar acting as an effective lubricant. Opuntia cladode fiber and biochar influenced water absorption rates, mitigated by silane surface treatment. The biocomposites show promise for electronics, spacecraft, automotive components, and packaging. The specific problem addressed is the need for sustainable materials. Opuntia cladode fiber and palm flower biochar offer a focused solution, yielding composites with improved mechanical, thermal, and water absorption properties for targeted industrial applications.

Equitable Machine Learning for Hypoglycaemia Risk Management.

We developed a machine learning (ML) model for the detection of patients with high risk of hypoglycaemic events during their hospital stay to improve the detection and management of hypoglycaemia. Our model was trained on data from a regional local health care district in Australia. The model was found to have good predictive performance in the general case (AUC 0.837). We conducted subgroup analysis to ensure that the model performed in a way that did not disadvantage population subgroups, in this case based on gender or indigenous status. We found that our specific problem domain assisted us in reducing unwanted bias within the model, because it did not rely on practice patterns or subjective judgements for the outcome measure. With careful analysis for equity there is great potential for ML models to automate the detection of high-risk cohorts and automate mitigation strategies to reduce preventable errors.

Cationic regulation of specificity and activity of defective MCo2O4 nanozyme (M=Fe, Co, Ni, Cu) for colorimetric detection of caffeic acid

Spinel oxide has great promise in constructing highly active nanozymes due to its tunable crystal structure. However, it still faces the problems of poor specificity and insufficient enzyme activity, which limits its application in the field of analysis. Herein, a series of transition metal spinel oxides were synthesized by cation regulation strategy, and their enzymatic activity and catalytic mechanism were analyzed. Interestingly, FeCo2O4, Co3O4 and NiCo2O4 had oxidase-like activity and peroxidase-like activity, while CuCo2O4 had specific and high oxidase-like activity. Their oxidase-like activities follow the order of FeCo2O4 < Co3O4 < NiCo2O4 < CuCo2O4, which is consistent with their cation radius. The smaller the cation radius of tetrahedral site, the more beneficial it is to increase the oxidase-like activity. The high oxidase-like activity of CuCo2O4 may be attributed to the production of 1O2, •O2− and •OH. EPR results showed the presence of abundant oxygen vacancies in CuCo2O4. Upon the introduction of EDTA, TMB color reaction fades because of oxygen vacancies elimination by EDTA, indicating that oxygen vacancies played an important role in the reaction. Based on the inhibition effect of caffeic acid on the high oxidase-like activity of CuCo2O4, a simple and sensitive caffeic acid colorimetric sensing platform was developed. The linear range for the detection of caffeic acid is 0.02–15 μM, with a detection limit as low as 13 nM. The constructed sensor enables the detection of caffeic acid in caffeic acid tablets and actual water samples, providing a new strategy for the detection of caffeic acid and drug quality control.

Unrelated Parallel Machine Scheduling Problem Considering Job Splitting, Inventories, Shortage, and Resource: A Meta-Heuristic Approach

This research aims to study a real-world example of the unrelated parallel machine scheduling problem (UPMSP), considering job-splitting, inventories, shortage, and resource constraints. Since the nature of the studied optimization problem is NP-hard, we applied a metaheuristic algorithm named Grey Wolf Optimizer (GWO). The novelty of this study is fourfold. First, the model tackles the inventory problem along with the shortage amount to avoid the late fee. Second, due to the popularity of minimizing completion time (Makespan), each job is divided into small parts to be operated on various machines. Third, renewable resources are included to ensure the feasibility of the production process. Fourth, a mixed-integer linear programming formulation and the solution methodology are developed. To feed the metaheuristic algorithm with an initial viable solution, a heuristic algorithm is also fabricated. Also, the discrete version of the GWO algorithm for this specific problem is proposed to obtain the results. Our results confirmed that our proposed discrete GWO algorithm could efficiently solve a real case study in a timely manner. Finally, future research threads are suggested for academic and industrial communities.

Nanoencapsulation of green tea catechin (−)-Epigallocatechin-3- Gallate (EGCG) in niosomes and assessment of its anticancer activity against lung cancer

Lung cancer is one of the leading causes of cancer-related deaths worldwide. In chemotherapy, the use of strong cytotoxic drugs and the specificity problems of these drugs also affect healthy cells and tissues. For this reason, the purpose of cancer treatment is to ensure that a suitable drug directly affects cancer cells at the appropriate dose. With nanotechnology, steps have been taken for an effective treatment that develops nano-transporters to deliver the drug molecule to the target cell in a specific, controlled manner. Another development is the discovery of theranostic agents used for both diagnostic and therapeutic purposes. In this study, a smart molecule was developed using the anticancer and antioxidant Epigallocatechin-3-Gallate (EGCG) molecule found in green tea, which is commonly consumed in our society. This molecule was encapsulated with niosomes to increase its stability and specificity. In this study, niosomes with an average size of 150 nm were synthesized using the thin film hydration technique. The zeta potential value of niosomes varied between −25 mV and −30 mV. Niosomes have been functionalized with indocyanine green (ICG) fluorescent dye and made suitable for optical imaging. The encapsulation efficiencies of the EGCG molecule and the ICG fluorescent dye were 10.1 % and 34.4 %, respectively. The release of EGCG from niosomes was an initial fast and then a slower release. 32 % of EGCG was released from niosomes within the first 3 h. Also, Cetuximab molecule was conjugated to niosomes with 75.8 % efficiency in order to provide lung cancer specificity and increase the anticancer effect. DLS, FTIR, XPS and TEM were used in the characterization phase of nanoparticles. While DLS and TEM provide information about dimensional analysis, FTIR and XPS were performed to verify the conjugations. Cytotoxicity, apoptosis, fluorescence imaging and incorporation studies of the molecule design created for theranostic purposes in A549 lung carcinoma and BEAS-2B normal bronchial epithelial cells were examined in vitro. As a result of these studies, it was determined that the synthesized molecule design has more involvement, toxic and apoptotic effects on A549 lung carcinoma cells. In this study, the therapeutic efficacy of the synthesized niosomal molecule design on the target cell and its potential to be used in cancer treatment were revealed and it is thought that it will contribute to the field of biotechnology.

A few special problems of meromorphic functions share values in part with their shifts and derivatives

A few special problems of meromorphic functions share values in part with their shifts and derivatives