The global accumulation of mine tailings, particularly those generated from nickel mining operations, poses substantial environmental hazards due to the presence of leachable heavy metals (HMs). Among the emerging remediation techniques, stabilization/solidification via geopolymerization offers a promising circular strategy by transforming hazardous waste into
valuable construction materials while immobilizing toxic contaminants. This study investigates the potential of nickel mine tailings (NMT) as a precursor for geopolymeric binders, in combination with supplementary cementitious materials (SCMs) including ground granulated blast furnace slag (GGBFS), coal fly ash (CFA), and limestone powder (LP), incorporated at 75
wt%, 50 wt%, and 25 wt% ratios. Sodium hydroxide (NaOH) and calcium hydroxide (Ca(OH)₂) were used to initiate geopolymerization. The result showed that near absence of aluminosilicates in nickel mine tailing presents inadequacy of the material as standalone precursor for preparation of geopolymer. Hence, the addition of supplementary materials as sources of alumina and silica demonstrated favorable engineering properties. Highest 28-day compressive strength of 20.05
MPa was achieved in sample containing 75wt% GGBFS via Ca(OH)2 activation, attributed from C-A-S-H and C-S-H formation, while comparable strength of 14.32 MPa was attained in sample activated by NaOH. Optimized mix ratio for CFA-based sample of 75wt% CFA, NaOH-activated yielded a 28-day compressive strength of 13.01 MPa. These strengths fall within the acceptable range for load-bearing mortar application as per ASTM standards. Samples have also demonstrated HM immobilization rates, as high as 99.9859%, 99.9995%, and 99.9380% for Ni, Mn, and Cr, respectively. In addition, NaOH-based activation presented more resistance to HM remobilization and acid attack due to strong alkalinity and ability to synthesized to denser matrices. This study implies the potential of NMT-based geopolymer as construction and building material based on its evaluated mechanical and leaching properties.

This study investigates the effect of coexisting iron (Fe(III)) on nickel recovery using Fluidized Bed Homogeneous Crystallization (FBHC) technology. A Box–Behnken experimental design was employed to evaluate the influence of pH (8.5–9.5), precipitant-to-metal molar ratio (carbonate/nickel ion) (1.5–2.0), and iron concentration (0.36–1.07 mM) on nickel removal and granulation efficiency. It has fixed factors of Ni(II) (5.11 mM), flowrate (10 mL/min), and gradual increase of reflow rate (120 mL/min). Results showed that elevated pH and molar ratio enhanced nickel recovery (>96%) through increased supersaturation and nucleation kinetics. Iron played a multifaceted role—moderate concentrations (~0.72 mM) enhanced crystallization by serving as scaffolds for nucleation, while excessive iron disrupted crystal structure and surface passivation.

Comprehensive characterization (FTIR, Raman, XRD, SEM-EDS, XPS, TGA) confirmed the formation of NiCO₃, Ni(OH)₂, FeOOH, and Ni–Fe layered double hydroxides (LDHs). Kinetic analysis revealed that the pseudo-second-order mechanism dominated the crystallization process. Thermodynamic analysis indicated that moderate Fe(III) levels improve the thermal stability of the granules. This work highlights the potential of FBHC in treating complex multi-metal wastewater, providing a pathway for high-purity nickel recovery, and reduced sludge generation.

The oxygen evolution reaction (OER) is a crucial step in water electrolysis for sustainable hydrogen production. However, the dependence on noble-metal catalysts like IrO2 and RuO2 limits scalability due to their high cost and scarcity. This study aims to develop a cost-effective and sustainable OER electrocatalyst by synthesizing a bimetallic Bi-Fe/N-doped carbon (Bi-Fe/NC) catalyst derived from zeolitic imidazolate framework-8 (ZIF8). By leveraging Fe-Bi interactions and nitrogen-doped carbon support, this research explores an economically viable approach for improving OER efficiency in non-noble electrocatalyst.
The catalyst was synthesized via a one-pot solvothermal method at 120 °C for 4 h, followed by pyrolysis. The study examined the effects of pyrolysis temperature, Bi to Fe ratio, and metal-to-ZIF8 ratio on catalytic performance. Higher pyrolysis temperatures enhanced conductivity and electrochemically active surface area (ECSA), while an optimal 2:8 Bi-to-Fe ratio improved graphitization and active oxide formation. Additionally, in an effort to remove oxides without acid treatment, lower metal loading (0.025) resulted in reduced OER activity due to fewer active sites. The optimized Bi2Fe8NC 0.05 catalyst exhibited an overpotential of 397.48 mV at 10 mA cm-2 and a Tafel slope of 80.61 mV dec-1 in 1.0 M KOH, highlighting electronic conductivity and ECSA as the dominant factors influencing OER performance. Stability tests showed a 21.20% increase in overpotential after 2000 cycles and stable chronoamperometric performance for 7.5 h before noticeable degradation. These findings highlight Bi-Fe/NC catalysts as promising alternatives to noble-metal-based OER catalysts. However, long-term stability remains a challenge, likely due to metal oxide leaching and structural degradation. Future studies should focus on enhancing catalyst durability and employing computational methods to further investigate
reaction mechanisms.

Nonlinearity in communications systems negatively impacts its performance. In radio over fiber systems, lasers are one of the primary contributors to link nonlinearities. There are existing major techniques in link linearization, namely, hardware compensation, and digital signal processing (DSP). DSP offers promising link performance at a lower cost. Improvements in the computational time and complexity of the system are needed for the system to adapt with the conditions of the link close to real-time.

The dissertation aims to characterize and linearize two different Intensity Modulation - Direct Detection RoF systems and analyze the degree of nonlinearity caused by the laser diode. Models are used to create a DSP-aided RoF link linearization, exploring the different techniques: predistortion, postdistortion, and dual compensation. The links are electronically linearized by estimating the predistortion through Memory Polynomial Method (MP) and Generalized Memory Polynomial Method (GMP), improved through the novel implementation of the Improved Cann Model as postdistortion, and a combination of the two techniques through dual compensation.

In digital predistortion, ACPR improved by 5 dB, and EVM improved by up to 11%. Memory effects were observed to be mitigated as well in the AM-AM and AM-PM plots. This technique requires initial training and high memory depth with increased computation time and complexity. Performance improvement using the novel digital postdistortion is
seen in the EVM of the link, with as much as a 12% difference from the original received OFDM signal, improving the scatter and correcting memory effects. Improvements observed in the system are limited to in-band signals. Dual compensation proposed improved both in-band and out-of-band signals, yielding the best ACPR values, despite having a lower memory depth with approximately 7 dB improvement. Application of the postdistortion reduces computational complexity in the predistorter, lowering the memory depth required to have a better performance of the link.

Autoimmune diseases arise from immune-mediated attacks on healthy tissues, driven by autoantibodies that target self-antigens and amplify inflammation through sustained activation of the Janus kinase/signal transducer and activator of transcription (JAK/STAT) pathway. Pro-inflammatory cytokines, often elevated in autoimmunity, hyperactivate JAK/STAT signaling, which in turn promotes autoreactive B and T cell responses, further increasing autoantibody production. This self-reinforcing cycle disrupts immune tolerance, perpetuates tissue damage, and accelerates disease progression, highlighting JAK/STAT as a critical node linking autoantibody-driven inflammation to autoimmune pathogenesis. While JAK inhibitors have proven effective in controlling such diseases, their clinical use has been limited by adverse effects, including increased risks of infections, cardiovascular events, and certain cancers.
This study aimed to identify potential inhibitors of Janus kinases (JAK1, JAK2, JAK3, and TYK2), key components of the JAK/STAT pathway, by screening 2,607 phytochemicals from the MMRL virtual library. ADMETLab 3.0 was used to filter compounds based on drug-likeness and safety properties, and 24 candidates met all criteria for further analysis. Molecular docking analyses using AutoDock 4.2 and AutoDock VINA revealed that five promising candidates—cycloeicosane, ambrettolide, (10Z)- oxacyclononadec-10-en-2-one, (Z)-oxacyclopentadec-6-en-2-one, and myricetin 3- rutinoside—have competitive docking scores across all JAK kinases, comparable to or exceeding those of reference drugs such as peficitinib, upadacitinib, and tofacitinib. Molecular dynamics simulations indicated that these five phytochemicals are stable when in complex with the four Janus kinases within the 100-ns simulation timeframe. Hydrogen bond heatmaps highlighted the unique ability of myricetin 3-rutinoside to form consistent hydrogen bonds, while other candidates primarily relied on hydrophobic interactions. The MM/PBSA results revealed that cycloeicosane exhibited the strongest binding affinity across all JAK kinases—JAK1 (-40.31 kcal/mol), JAK2 (-38.70 kcal/mol) JAK3 (-38.69 kcal/mol), and TYK2 (-35.54 kcal/mol). Myricetin 3-rutinoside, ambrettolide, (Z)- oxacyclopentadec-6-en-2-one, and (10Z)-oxacyclononadec-10-en-2-one also showed competitive binding affinities. Based on these findings, cycloeicosane, ambrettolide, (10Z)-oxacyclononadec-10-en-2-one, (Z)-oxacyclopentadec-6-en-2-one, and myricetin 3- rutinoside are recommended for further in vitro and in vivo evaluations to validate their inhibitory potential against JAK kinases, paving the way for the development of novel therapeutics for autoimmune diseases.