Geothermal scale powder (GSP), a waste generated from geothermal power plants, was investigated as a filler to improve material properties of stereolithography (SLA) resin. Simultaneously, low cost unsaturated polyester (UP) resin characterized with excellent mechanical properties was employed for photopolymerization. The addition of GSP to neat SLA resin enhanced the flexural modulus by 22% and Shore D hardness by 4%; however, poor dispersion and agglomeration of GSP in the matrix reduced the flexural strength by 10%. Hence, GSP was surface-modified with surfactants, such as stearic acid (SA) and glycerol monostearate (GMS), and silane coupling agent 3-trimethoxysilylpropyl methacrylate (TSPM). Flexural modulus and Shore D hardness of SLA resin were improved by 73% and 13%, respectively, with the addition of GSP modified with 3 wt% TSPM, while flexural strength decreased by 23% due to inefficient reaction of TSPM. Development of UV-cured UP resin showed maximum cure depth at optimal photoinitiator loading of 1 wt% benzil. Addition of co-initiators such as cocamide monoethanolamine
(CMEA) enhanced the average cure depth by 5%, while cocamide diethanolamine (CDEA) shifted the optimal photoinitiator loading to 0.5 wt% benzil and enhanced the average cure depth by 15%. Addition of CMEA or CDEA also improved the hydrophobicity of UV-cured UP resin by 12%. Standard design equation for stereolithographic parameters was also employed to assess and optimize the reactivity of UV-curable UP resin. Essentially, flexural properties and hardness of optimized UV cured UP resin were significantly higher than commercial SLA resin. Finally, 120% increase in flexural modulus, 7% increase in
flexural strength and 20% increase in hardness was obtained with TSPM-modified GSP/UP resin composite.

The DNA sequence serves as the fundamental blueprint of life, offering potential for biological discovery through computational analysis. With the continuous decline in sequencing costs, genomic data are being generated at an unprecedented rate—attracting not only researchers but also potential threats from malicious actors. Sensitive genetic information can be exploited in various ways, such as discrimination based on disease predisposition or blackmail involving participation in genomic studies. These concerns highlight the urgent need for secure and efficient DNA data protection. While existing approaches utilize both general-purpose and DNA-specific encryption methods, encryption alone can impose substantial computational overhead, thereby underscoring the necessity of integrating compression techniques to enhance efficiency. This study introduces Biitroot, a novel approach that combines k-mer–based compression with Advanced Encryption Standard (AES) encryption. Compression efficiency is optimized by tuning k-mer lengths, encoding schemes, and key-handling mechanisms across organisms and sequence sizes. Biitroot achieves file size reductions of up to 75%, outperforming the 67% reduction achieved by the reference method, Cryfa. Furthermore, Biitroot supports batch compression with independent per-sample processing, allowing de-compression of individual files without accessing others. Additional capabilities include customizable AES modes, support for the extended DNA alphabet, and secure management
of both compression and encryption keys.

This study explored the valorization of cashew nut shell (CNS) cake, an agro-industrial by-product, through oxidative torrefaction to enhance its performance as a solid biofuel. Despite their abundance, CNS cakes remain underutilized for energy applications. Oxidative torrefaction, a thermal treatment in the presence of limited oxygen, was conducted at 200, 250, and 300°C for 20, 40, and 60 minutes to assess changes in the fuel properties. The process significantly altered the lignocellulose composition: mainly extractives and hemicellulose were reduced, while cellulose and lignin were concentrated, improving the combustion behavior. Fuel quality was enhanced by reductions in moisture and volatile matter (75.64% to 41.40%) along with oxygen and hydrogen, and increased in fixed carbon (22.89% to 55.43%) with carbon. The 300°C for 20 minutes condition was identified as optimal, achieving the highest energy–mass co-benefit index (EMCI) of 20.64%, with a higher heating value (HHV) of 24.34 MJ/kg, energy density ratio (EDR) of 1.28, mass yield (MY) of 72.46%, and energy yield (EY) of 93.10%. Torrefying beyond this point led to marginal HHV gains, but significant losses in fuel mass and energy retention, indicating diminishing returns. Thermogravimetric analysis showed that severe torrefaction improved thermal stability and reduced reactivity, whereas less severe conditions provided better ignitability. These results demonstrate that oxidative torrefaction transformed the structural and physicochemical components of the CNS cake, enhancing the bioenergy potential and combustion profile, while maintaining a substantial portion of usable fuel. This approach offers a much lower ash and emissions alternative to fossil fuels. Moreover, valorizing the CNS cake through torrefaction supports viable waste management and contributes to circular bioenergy systems.

A user’s participation in a study leads to his/her personal and possibly sensitive data to be stored in a statistical database, where data analysts can perform calculations and then extract useful information. Privacy is guaranteed through generic, one-size-fits-all privacy policies defined by service providers, which could still leave the data of the end-users vulnerable. This problem is solved by -differential privacy, wherein noise (as a function of the constant privacy parameter ) is added to the aggregated data to protect individual users and provide them an avenue to deny their participation in the study. However, not all pieces of data have the same weight, and users may also have differing definitions of privacy and how much risk they are willing to take in case their data is exposed. This study looks at -differential privacy when applied locally, or on the side of the users, so that they could have full control over how much of their real data they are actually giving up, before it even reaches the ones collecting the data. By varying the distribution of cautious users (who require more privacy and a lower) to those more tolerant to risk (higher ), we see which local differential privacy mechanisms were as effective as the centralized differential privacy mechanisms when applied to a particular type of variable, and which are not.

Volatile organic compound (VOC) emissions have become a key air pollution concern due to adverse health and environmental effects. The refractory nature of organic compounds combined with the toxicity of secondary metabolites limit the physical-chemical treatment processes and conventional biological processes. To overcome these drawbacks, the development of innovative advanced oxidation processes (AOPs) for the degradation of gaseous organic compounds is of major interest.
This work presents the results of two AOPs in the degradation of gaseous VOCs (toluene as a representative compound) – UV irradiation with ozonation (UV/O3) and ultrasonication (US) – considering various operating parameters such as initial toluene concentration, ozone dosage, and ultrasound frequency. For the UV/O3 process, increase in inlet concentration resulted to a decrease in toluene removal while increase in ozone dosage lead to a higher removal. An additional water scrubbing step for the UV/O3 process enhanced the abatement up to 99% due to solubilization of ozone and further oxidation of contaminants. For the US process, increase in inlet concentration had varying effects at different frequencies. Increase in US frequency and additional water recirculation lead to an increase in the removal efficiency. However, addition of ozone proved to be inhibitory for the process. In comparison, UV/O3 proved to be more efficient in terms of toluene removal at lower inlet load while US resulted to higher elimination at higher loading.